Today, we’re excited to share a long-term commitment to the Department of Energy’s (DOE) Genesis Mission, backed by a $60 million investment designed to accelerate AI for science and the breakthroughs it can deliver for the country. This deepened commitment includes Microsoft’s new Scientific Partnership Advancing Research & Knowledge coordination hub and program office, otherwise known as SPARK, that is focused on facilitating collaboration and scientific discovery for the Genesis Mission.

The Genesis Mission represents an ambitious vision, bringing together DOE’s 17 National Laboratories, world-class experimental facilities, decades of irreplaceable scientific data and next-generation computing into a single, unified platform capable of transforming how science gets done. The critical goal of the Genesis Mission is to double the productivity and impact of American research and innovation within a decade by embedding AI directly into the scientific process. It’s a bold step forward and exactly the kind of moonshot that defines American science.

At Microsoft, we believe that this goal is not only achievable, but also essential as a national security imperative and an economic engine for generations to come. With this commitment and the launch of SPARK, we’re ready to partner fully in this mission and build on our collaborations across government and with academia.

Microsoft investing in AI for science

Today, Microsoft’s $60 million investment package will begin to accelerate AI for science in support of DOE and the National Laboratories. As sustained scientific impact requires more than infrastructure alone to enable lasting scientific outcomes, Microsoft’s investment package is structured in two parts:

• $40 million in Azure compute and AI credits, distributed over three years, to power the large-scale AI and scientific workloads at the heart of the mission. This gives researchers room to train, simulate and iterate at a scale that matches their ambition.
• $20 million in solution engineering enablement services. Dedicated engineering, architecture, deployment, adoption and acceleration support to turn cloud and AI capacity into operational scientific outcomes. This investment helps ensure that the Genesis Mission advances in practice and in principle.

Together, this investment reflects a simple conviction: While infrastructure opens the door, it is people, expertise and disciplined delivery that carry discoveries across the finish line. Microsoft is committing to both.

Introducing SPARK: Microsoft’s catalyst for advancing scientific partnerships

Great partnerships need more than good intentions and good technology — they need a clear way to work together. So, alongside this commitment, we are standing up a new program office and coordination hub: SPARK, or Scientific Partnership Advancing Research & Knowledge.

SPARK is the single front door and coordination hub for Genesis Mission collaboration with Microsoft. SPARK orchestrates the full breadth of what Microsoft brings to bear: program, technical, research, engineering, security, compliance, partner and field teams into one clear, consistent path from first idea to deployed science.

SPARK is built around five commitments:

• A dedicated Genesis Mission Program Management Office. This office handles intake, prioritization, a disciplined sprint-and-checkpoint cadence and a steady operational interface with DOE for alignment, reporting and sustained partnership.
• An AI for Science Center of Excellence. An integrated delivery team that moves use cases from concept to secure, compliant, scalable implementation, with enablement through office hours, hackathons and training grounded in responsible AI and reproducible research.
• Optimization of Azure credits. Ensures computing resources are directed toward the projects where they can accelerate science most.
• Management of technical services. Dedicated support to help labs adopt and operationalize AI-for-science capabilities, delivered by Microsoft teams and select partners.
• Joint research and development. A focused set of Genesis Mission-aligned challenge problems, co-developed by Microsoft researchers and DOE scientific leadership, with milestones, publications and IP governed by mutually agreed terms.

Underneath SPARK sits the full breadth of Microsoft’s secure, FedRAMP-authorized cloud and AI portfolio. This includes Microsoft Azure infrastructure, Microsoft Foundry and Zero Trust security through Microsoft Defender, Sentinel and Entra. Azure capabilities will help extend the DOE’s American Science Cloud capabilities by providing computing, AI, data and collaboration services that complement existing scientific infrastructure. Together, these capabilities will help accelerate discovery, enable secure collaboration across institutions and provide researchers with flexible access to advanced technologies and resources. This will enable DOE and National Laboratory scientists to move faster from hypothesis to discovery, without compromising the security, reproducibility and governance that mission-critical research demands.

Accelerating science with Microsoft Discovery and Quantum

Microsoft’s new commitments build on capabilities we recently announced through Microsoft Discovery and Microsoft Quantum. They are designed to accelerate scientific research and will support the Genesis Mission’s ambition to bring AI, advanced computing and emerging technologies more deeply into the scientific process.

To enable a unified research platform for Genesis Mission work, Microsoft will provide access to Microsoft Discovery, our integrated platform that unites AI models, simulation, data and experimental workflows driven by advanced cognition rooted in scientific method, within a single governed environment. Microsoft Discovery, now generally available, includes support for autonomous lab orchestration, integration of Microsoft Research’s AI models for science, continuous AI learning through the scientific loop and agentic memory, advances in Discovery Bookshelf for data curation and scalable indexing and deeper integration and multi-hop reasoning over enterprise science data estates, including data governance. Together, these capabilities are designed to help researchers move more quickly from data to insight, from simulation to experiment, and from promising idea to scientific breakthrough.

We also recently announced the preview of the Microsoft Discovery app, a local desktop experience that helps researchers, students and scientific teams begin working with Microsoft Discovery today. Our support for the Genesis Mission will include access to the Microsoft Discovery app to enable DOE and National Laboratory teams with early access to its capabilities.

Microsoft’s recent quantum progress further strengthens the foundation for Genesis Mission work. With Majorana-based quantum advances, including more reliable topological qubits and a roadmap toward scalable quantum computing, Microsoft is helping move quantum from long-range research toward practical scientific capability. For DOE and National Laboratory teams, that progress can open new ways to model complex materials, chemistry, energy systems and national security challenges that are difficult or impossible to solve with classical computing alone. Just as important, the same agentic AI for science approach behind Microsoft Discovery is helping accelerate quantum research itself, creating a reinforcing cycle in which AI speeds quantum breakthroughs and quantum computing expands what scientists can ultimately discover.

The work is already underway

Working alongside and supporting federal researchers and universities, we’re already seeing real-world impact, from faster materials screening to advanced biosurveillance modeling. Four of the first projects taking shape under this partnership show what that looks like in practice:

Discovering critical energy storage materials and biosystems design (Pacific Northwest National Laboratory)
Using AI to dramatically accelerate the discovery of new energy storage materials through novel experimentation design and shrinking analysis of massive volumes of scientific data from years to weeks. In biosystems design, Microsoft Discovery is plugging directly into PNNL’s laboratory automation infrastructure to launch self-driving scientific workflows that autonomously design, run and fine-tune biological experiments in real time.

Strengthening biosecurity (Lawrence Livermore National Laboratory)
Pairing advanced AI with modern bioinformatics to identify emerging biological threats sooner and develop responses faster, strengthening the nation’s ability to stay ahead of the next outbreak and developing proactive defenses against evolving biosecurity risks. By applying advances in AI, scientific computing and biotechnology, Microsoft and the Lawrence Livermore National Laboratory are helping strengthen the nation’s ability to prevent, detect and respond to biological threats, advancing US biosecurity and biodefense priorities while supporting the long-term resilience and competitiveness of the US bioeconomy.

Autonomous labs for accelerated materials discovery (Johns Hopkins University Applied Physics Laboratory)
Supporting the development of AI-enabled autonomous (“self-driving”) laboratories through the integration of advanced foundation models and simulation tools — including MatterGen and MatterSim — to rapidly design, execute and optimize experiments for structural materials and superconductors. By combining autonomous experimentation with accelerated computational materials discovery, this approach dramatically shortens the path from scientific hypothesis to validated, manufacturable, mission-enabling materials, while exploring a vastly larger design space than is possible through traditional methods.

Accelerating nuclear energy permitting and autonomous energy operations (Idaho National Laboratory)
Applying AI to streamline the licensing, permitting and review of new nuclear projects. AI helps automate the development of complex engineering and safety analysis materials, a historically time-consuming and expensive process, to get this critical documentation into the hands of regulators and safety reviewers sooner. The lab also demonstrated that secure, distributed, hyperscale cloud can enable autonomous remote operations for nuclear power generators. Together, these efforts are helping bring safe and reliable power online faster and ensure scalable, efficient and reliable operations to meet the nation’s surging demand for energy.

Why this matters

We are entering an era where AI and quantum don’t just support the scientific process — they are essential to it. Through the Genesis Mission, Microsoft is committing to work as part of America’s research enterprise by providing hyperscale compute, advanced models, emerging quantum capabilities and dedicated expertise that run alongside the labs’ own world-leading systems. We are helping to ensure that the nation’s scientific strength is built on American technology. This commitment builds and expands upon the decades of collaboration through Microsoft Research and partnerships across the US government and our national labs. Now is the time to scale these breakthroughs across the entire R&D ecosystem.

The mission ahead is significant, and it should be. Whether it’s advancing the frontiers of energy, chemistry and materials science, hardening our national security or simply giving the country’s best scientists better tools to ask bigger questions, this is work worth doing and worth doing together. With a $60 million investment and SPARK, Microsoft is ready to help ensure America’s scientific leadership continues to accelerate.

Fueling scientific discovery is one of the most important things these technologies can do. AI and quantum are transforming how we tackle the toughest challenges facing the country, from sustainable materials and clean energy to biosecurity and drug discovery. The Genesis Mission is a pivotal step toward advancing that progress. We commend the DOE’s vision in building a unified, holistic approach to these critical national missions. For America to seize this opportunity and set the global standard, we must put these breakthrough technologies to work advancing the nation’s research and development.

We’re ready to deepen this partnership across government and academia. We move faster together. I’ve never been more optimistic about what’s possible when the nation’s scientific talent meets the best of modern AI and quantum. The Genesis Mission is that moment. Let’s get to work.

To get started, reach out to your Microsoft account team or email genesismission@microsoft.com.

Chris Barry leads Microsoft’s US Public Sector business. He partners with federal, state and local government and higher education agencies and organizations to accelerate digital transformation, bringing Microsoft’s secure cloud and AI capabilities to mission-critical work that serves communities across the nation.

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AI workloads are scaling faster than any single infrastructure approach can support — with more models, new agent-driven workloads and surging compute demand driving the need for greater specialization across the stack. To meet this need, Microsoft continues to evolve Azure’s infrastructure, including expanding its AI fleet with AMD’s most advanced AI and high-performance computing (HPC) solutions.

Our approach to AI infrastructure is designed to support the breadth of how AI systems are built and run. We closely work with industry innovators like AMD as well as our own purpose-built silicon and systems to provide customers with a comprehensive, open and heterogenous platform to achieve the best performance, cost and energy efficiency outcomes.

Building on our close collaboration with AMD, Microsoft is bringing AMD’s latest Helios AI platform and next-generation EPYC datacenter processors to Azure. These technologies will power three upcoming Azure offerings: HDv2 VMs for data processing, HXv2 VMs for electronic design automation (EDA) and ND MI455X v7 VMs for AI inference workloads.

Expanded infrastructure for inference, AI data systems and chip design

Built for AI data systems — Azure HDv2

CPU infrastructure is essential to the performance and efficiency of modern AI systems. AI accelerators depend on high-density, power-efficient CPU compute to process data, coordinate workloads and keep pipelines running at scale. Without this, training jobs don’t have enough data to learn from, and agents don’t have enough capacity to perform tasks on behalf of customers. Azure HDv2 virtual machines are one of our latest offerings designed from the ground up to eliminate these bottlenecks and empower massive agentic workload adoption.

Co-designed with AMD, HDv2 VMs expand Azure’s portfolio of purpose-built solutions for the most demanding CPU workloads from AI customers, including data preparation, search, reinforcement learning and agent coordination at scale. Featuring nearly 500 physical 6^th Gen AMD EPYC CPU cores, 4 terabytes of RAM, 32 terabytes of local NVMe storage and 400 Gb Azure Boost networking, HDv2 VMs are built for the workload needs of our most demanding AI customers.

Optimized for silicon design and technical computing — Azure HXv2

The AI era has created tremendous need and opportunity for firms developing the silicon products that power this infrastructure. For this reason, Azure HX virtual machines, launched in partnership with AMD in 2023 and featuring AMD’s unique 3D V-cache technology, have seen significant adoption among silicon design firms working to bring more capable and efficient AI silicon to market. Today, we are announcing the next step in our workload optimized journey for these customers, HXv2.

HXv2 virtual machines build on and extend the strengths of HX. They both continue the differentiation Azure offers for RTL simulation workloads by again employing 3D V-cache technology, while offering significant improvements to single threaded performance and memory. HXv2 VMs will feature 176 AMD 6^th Gen EPYC CPU cores with a clock frequency of more than 5 GHz, 50% more addressable cache per core and VM sizes with nearly 2 or 4 terabytes of RAM, helping customers optimize their workloads to memory needs.

Azure HXv2 is also designed to support a broader range of technical computing workloads including scientific simulation, engineering analysis and other distributed memory applications. The significantly increased per VM and per core performance, and the inclusion of 800 Gb InfiniBand, enable large-scale MPI-based simulations and make HXv2 an ideal fit for a wide variety of HPC customers.

AMD, a leading HX-series customer, highlights this impact directly:

“Engineering teams are pushing the limits of simulation, chip design and scientific computing. At AMD, we experience those demands firsthand as we design future AMD EPYC CPUs and AMD Instinct GPUs. Azure HX is an important platform for scaling complex EDA workloads, and we’re excited about Azure HXv2, which is designed to deliver even greater performance and scalability. We look forward to continuing our collaboration with Microsoft as we help advance infrastructure for the world’s most demanding engineering and scientific workloads.”

— Mark Papermaster, Executive Vice President and CTO, AMD

The HXv2 also leverages Microsoft’s long-standing collaboration to optimize Synopsys AI-powered EDA solutions on Azure:

“As AI compute continues to push the limits of semiconductor design, our collaboration with Microsoft on the Azure HX-series demonstrates a shared vision for enabling customers to deliver next-generation AI systems with precision and scale in accelerated design cycles. These systems have enabled Synopsys customers to reliably and efficiently leverage cloud-based compute, extending EDA workloads beyond traditional infrastructure constraints so they can meet ambitious development schedules while maximizing design quality and delivering dramatic performance gains.”

— Shankar Krishnamoorthy, Chief Product Development Officer, Synopsys

Production-scale AI inference — ND MI455X v7

ND MI455X v7 is designed for the reasoning, search and agentic workloads behind modern AI services. Powered by the AMD Helios rackscale solution, it expands Azure’s infrastructure options for large-scale inference and is designed to deliver strong performance and efficiency for demanding AI workloads.

Together, these new capabilities expand Azure capabilities while giving customers more flexibility to choose the right compute for each unique AI workflow: from inference, to data systems, to chip design. Customer choice is a core design principle built directly into Microsoft Azure, and we’re excited to bring AMD’s most advanced innovations at production scale.

To learn more about Azure’s high-performance computing and AI infrastructure capabilities, visit Azure.com.

Scott Guthrie is responsible for a set of hyperscale cloud computing solutions and services including Azure, Microsoft’s cloud computing platform, generative AI solutions, data platforms and information and cybersecurity. These platforms and services help organizations across the globe solve urgent challenges — and transform for the future.

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In 2026, reviewing Microsoft 365 security should not be seen as an IT housekeeping task. It is a business risk review. The question for owners and senior managers is simple: if someone gained access to your Microsoft 365 account today, what could they see, send, delete or steal?

The good news is that many of the most important protections are already available within Microsoft 365. The challenge is making sure they are switched on, configured properly and reviewed regularly.

Why Microsoft 365 Security Settings Matter to SMEs

Cyber criminals do not only target large enterprises. SMEs are often attractive because they may have valuable data, regular payment activity and fewer dedicated security resources. A compromised mailbox can lead to invoice fraud, customer data exposure, reputational damage and operational disruption.

Microsoft 365 is secure when it is managed properly, but default settings are not always enough for today’s threat landscape. A yearly review helps confirm that your business has kept pace with staff changes, new devices, hybrid working, new applications and evolving cyber risks.

1. Multi-Factor Authentication: The First Line of Defence

Multi-factor authentication, often called MFA, adds an extra check when someone signs in. Instead of relying only on a password, the user also confirms the login through an app, security key or another approved method.

For senior managers, the business benefit is clear: a stolen password should not be enough to access company email, files or Teams. MFA is one of the simplest and most effective ways to reduce account takeover risk.

Management question: Is MFA enforced for every user, including directors, finance staff, administrators and remote workers?

2. Conditional Access: Sensible Rules for Safer Sign-ins

Conditional Access is a way of applying sensible rules to Microsoft 365 sign-ins. For example, your business may decide that staff can access email from approved countries, trusted devices or managed company laptops, while unusual sign-ins require extra checks.

This is useful because not every login attempt carries the same level of risk. A finance manager signing in from their usual laptop in the UK is very different from an unexpected sign-in from overseas at 2am.

Management question: Do your Microsoft 365 access rules reflect how your business actually works today?

3. Microsoft Defender: Built-in Protection That Needs Attention

Microsoft Defender helps protect Microsoft 365 users, devices and email from threats such as malware, phishing and suspicious activity. Depending on your licence, it can provide protection for email, endpoints and wider cloud activity.

The important point for business leaders is that having Defender available is not the same as having it properly configured. Policies, alerts and response processes need to be reviewed so that threats are blocked or acted on quickly.

Management question: Are alerts being monitored, and does someone know what to do when Defender flags a problem?

4. Secure Score: A Board-Friendly Security Health Check

Microsoft Secure Score gives your organisation a measurable view of its Microsoft 365 security posture. It highlights recommended actions and helps track improvement over time. For senior managers, it can turn a complex technical topic into a more manageable business dashboard.

A higher score does not guarantee total protection, but it can show whether important settings are being ignored. It also helps create a prioritised improvement plan rather than relying on guesswork.

Management question: Do you know your current Secure Score, and is it reviewed as part of regular business risk management?

5. Backup: Microsoft 365 Is Not a Complete Backup Strategy

Many businesses assume that because their data is in Microsoft 365, it is automatically backed up in the way they need. Microsoft provides strong platform resilience, but that is not the same as a full business backup and recovery plan.

Accidental deletion, malicious deletion, ransomware, departed staff and retention settings can all create recovery challenges. SMEs should be clear about what can be restored, how far back they can go and how quickly the business could recover.

Management question: If a mailbox, SharePoint folder or Teams file library was deleted today, how quickly could you recover it?

6. Email Protection: Still the Front Door for Many Attacks

Email remains one of the most common ways criminals target SMEs. Fake invoices, supplier impersonation, password reset scams and malicious attachments can all arrive in an inbox looking convincing.

Good email protection should include spam and phishing filtering, attachment scanning, link protection where available, and correct domain settings such as SPF, DKIM and DMARC. Just as importantly, staff need to know how to report suspicious messages.

Management question: Are you actively reducing the risk of phishing and invoice fraud, or simply hoping staff will spot every fake email?

A Simple 2026 Microsoft 365 Security Review Checklist

• Confirm MFA is enforced for all users and administrators.
• Review Conditional Access rules for location, device and admin access.
• Check Microsoft Defender policies, alerts and response responsibilities.
• Review Microsoft Secure Score and agree priority actions.
• Confirm Microsoft 365 backup coverage, retention and restore testing.
• Review email protection settings, phishing controls and user reporting.
• Document who owns Microsoft 365 security inside the business.
• Schedule the next review before settings become outdated again.

Final Thoughts

Microsoft 365 is central to the way most SMEs operate, which is why its security settings should be treated as a business priority. A review does not have to be overly technical, but it should be structured, documented and repeated regularly.

For UK SME owners and senior managers, the goal is not to become cyber security experts. The goal is to ask the right questions, make sure the right protections are in place and reduce the chances of a preventable incident disrupting the business.

Call to action: If you have not reviewed your Microsoft 365 security settings recently, 2026 is the right time to start. A short review could identify simple changes that significantly improve your protection. Fruition stand ready to assist – contact us at helpdesk@fruitionsystems.co.uk.

Security | Fruition Systems | Microsoft Cloud Services in Hampshire

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Amy Coleman, EVP and Chief People Officer, shared the following communication with employees today.

When I stepped into this role, I promised to communicate more openly with you and share the “why” behind our decisions.

Today we are eliminating around 4,800 roles, about 2.1% of our global workforce, as we focus our people, investments, and energy on the priorities that will keep Microsoft positioned to deliver for customers in a fast-changing industry. The people whose jobs are impacted today are our colleagues and friends. They have made meaningful contributions to Microsoft, and we are deeply grateful for everything they have done.

Decisions like these are never easy, and you have my commitment that we are always looking for ways to reduce the need for job eliminations. Whenever possible, our priority is to place people into new roles aligned to the company’s highest priorities and greatest areas of opportunity. Over the past year, we have redeployed more than 4,000 employees into new roles, including another 500 this month. We will also transition four of our gaming studios to operate under new management, with the goal of preserving both their intellectual property and ongoing projects. In addition, more than 30% of eligible employees chose to participate in our recent voluntary retirement program, and we will continue exploring similar approaches in the future. While this doesn’t change the difficulty of today’s news, we will continue to do everything we can to create opportunities for our people, reduce the need for job eliminations where possible, and responsibly support those affected with care and respect.

The “why” is this: Our business is changing because the world around it is changing. The way technology is built, deployed, and used is transforming faster than at any point in my time here. Our customers’ needs are shifting, the business models that serve them are shifting, and that means the work itself – what we do, where we focus, and how we’re organized – has to transform too. Companies don’t get to choose whether their industry changes; they only get to choose whether they change with it. That means we will need to adjust resources and roles and shift how we operate so we can have the greatest impact for our customers.

I also want to be direct that the roles eliminated today are not being replaced by AI. At the same time, what is true is that AI is changing how work gets done. Some of the tasks we do every day can now be automated, and that means we all need to keep learning, keep building new skills, and keep adapting as the work evolves. Our customers are navigating this same shift, and they’re counting on us to help them through it. We can’t do that well unless we’re doing it ourselves. This comes down to two commitments: making the decisions needed to drive differentiated customer value, and supporting the people affected by them.

First, we will make the hard changes required to build differentiated products and services that deliver differentiated customer value. We are aligning our investment, people, and energy to our business priorities. Today’s changes mostly fall within our Commercial and XBOX organizations. In our Microsoft Commercial Business, they build on last week’s Frontier Company announcement, reshaping how we work and embedding our engineering experts alongside customers so we can help them accelerate their technology deployments. In XBOX, we are restructuring to position the business for long-term success. Engineering teams across the company will also evolve their structure and priorities to meet customer needs and innovate for the future.

Second, we will do this thoughtfully.  As mentioned above, we are working on alternative solutions to job eliminations, and beyond this, we will continue to invest in equipping employees with new skills, including in AI. For those who are impacted, we provide financial support and resources to help them take their next step.

I know many of you want to help those who are leaving but aren’t sure how. Reach out and check in on your colleagues. Use your network to bring people together, share what makes them exceptional, and help create connections to opportunities that might not happen otherwise.

We are still early on this journey, and there will be more changes ahead; other parts of our business will need to make similar changes. Each time, you can hold us to the two commitments.

During my time at Microsoft, I’ve seen this company reinvent itself again and again. What makes that possible has always been our people – their resilience, creativity, and willingness to keep learning.

Thank you for everything you bring to Microsoft.

Amy

Read more: Resetting XBOX.

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The good news is that you do not need to be technical to take sensible action. This guide explains what AI cyber attacks mean in plain English, why UK SMEs are attractive targets, and the practical steps business owners and senior managers should take to reduce risk.

Why AI has changed cyber crime

Traditional cyber scams often had obvious warning signs: poor spelling, strange wording, unusual email addresses or requests that simply did not sound right. AI has removed many of those clues. Criminals can now create emails, messages, invoices and even voice recordings that look and sound professional, personal and believable.

AI helps attackers research companies, write convincing messages, imitate tone of voice, translate content into perfect English and launch scams at scale. That means a small business can be targeted with the same level of sophistication once seen only in attacks against major organisations.

Why UK SMEs are at risk

SMEs are often attractive targets because they hold valuable data, make regular payments, work with larger customers and suppliers, and may not have a dedicated cyber security team. Criminals know that smaller businesses are under pressure, short on time and reliant on trusted relationships.

For an SME, one successful attack can lead to stolen data, fraudulent payments, operational downtime, reputational damage and loss of customer confidence. In some cases, the financial impact can be difficult to recover from.

The most common AI cyber threats facing SMEs

1. More convincing phishing emails

Phishing is still one of the most common ways criminals break into businesses. The difference is that AI-generated phishing emails can now be well written, highly personalised and relevant to your business. They may appear to come from a supplier, customer, colleague or senior manager.

2. Fake invoices and payment requests

AI can help criminals copy the style of real emails and documents. A finance team may receive a realistic request to change bank details, approve an urgent payment or settle an overdue invoice. These scams are designed to create pressure and bypass normal checks.

3. Voice cloning and deepfake calls

Criminals can use AI to imitate voices or create fake video content. A member of staff could receive what sounds like a call from a director asking them to make a payment, share login details or take urgent action. This is why relying on voice alone is no longer safe for high-risk decisions.

4. Faster attacks on weak systems

AI tools can help attackers find vulnerable systems more quickly. If software is out of date, passwords are weak or remote access is poorly protected, criminals may be able to identify and exploit those gaps faster than before.

5. Data theft and ransomware

AI can make it easier for criminals to identify valuable information and pressure businesses into paying. Ransomware attacks can stop access to files, systems and customer data, leaving the business unable to operate normally.

What senior managers should do now

Cyber security should not sit only with IT. AI-powered attacks often target people, processes and decision-making. Senior managers and business owners should treat cyber risk as a business risk, just like finance, health and safety or compliance.

• Introduce payment verification: Always confirm changes to bank details or urgent payment requests using a separate trusted method, such as a known phone number.
• Use multi-factor authentication: Add an extra layer of protection to email, cloud services, accounts and remote access.
• Keep software updated: Make sure devices, applications and security tools receive updates promptly.
• Train staff regularly: Focus training on realistic examples, including AI-written emails, fake invoices and voice scams.
• Back up important data: Keep secure backups and test that they can be restored.
• Limit access: Give staff access only to the systems and information they need for their role.
• Agree an incident plan: Decide in advance who does what if a cyber incident happens.
• Consider Cyber Essentials: The UK Government-backed Cyber Essentials scheme is a practical way to improve protection against common cyber threats.

Questions every SME leadership team should ask

• If someone requested an urgent payment today, how would we verify it?
• Do all key accounts have multi-factor authentication switched on?
• Could we operate if email or core systems were unavailable tomorrow?
• When did we last test our backups?
• Do our staff know how to report a suspicious message or call?
• Who would lead our response if customer data was compromised?

AI is not all bad news

It is important to remember that AI can also help businesses improve security. Modern tools can identify unusual behaviour, detect suspicious messages and support faster response. The key point for SME leaders is not to avoid AI, but to understand that criminals are using it too.

The bottom line for UK SMEs

AI cyber attacks are a serious and growing threat, but SMEs are not powerless. Most attacks still rely on familiar weaknesses: rushed decisions, weak passwords, poor verification, outdated systems and lack of preparation. By improving basic controls and making cyber security a leadership priority, UK SMEs can significantly reduce their risk.

If you are a business owner or senior manager, now is the time to review your cyber resilience. A short conversation today could prevent a costly incident tomorrow.

Need help protecting your SME from AI cyber threats?

If you are unsure where to start, begin with a practical cyber security review. Identify your biggest risks, strengthen your most important controls and make sure your people know what to do when something does not feel right. Fruition Systems can provide help and support for any aspect of Cyber Security – Security | Fruition Systems | Microsoft Cloud Services in Hampshire

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The pace of AI adoption is moving incredibly fast. Customers have moved well beyond experimentation and understand the importance of adopting AI to transform their business. They are now concentrating on delivering measurable business outcomes and demonstrating a return on their AI investments, while ensuring their intelligence is amplified and their IP is protected.

Today we are introducing Microsoft Frontier Company, a new operating business focused on delivering Frontier Transformation through AI for our customers around the world. It will provide a unique combination of skills inclusive of deep industry knowledge, change management and continuous improvement experience, and enterprise-grade AI engineering expertise. This goes beyond what has been labeled as Forward Deployed Engineering (FDE) and will be the largest, most capable, outcome-driven engineering organization in the industry. We are making a $2.5B investment in Microsoft Frontier Company, embedding 6,000 industry and engineering experts at customers to co-design, co-innovate, deploy and continuously improve AI systems at scale based on measurable business outcomes.

I recently wrote more about my conviction that Intelligence + Trust are the two most important components of any AI solution and how our customers can use different levers to manage cost.

Companies need to establish an intelligence platform so their unique IQ — their proprietary data, expertise, workflows and decision-making processes — compounds over time from within, using their choice of models to build AI solutions and workflows.

They need a trusted platform that allows them to observe, govern, manage and secure AI solutions across every layer of the technology stack, using FinOps to assess their ROI.

Enterprise AI engineering expertise with deep industry knowledge is required to build a system that acts as a continuous loop of improvement between the two platforms to fine tune agentic business processes, ensuring that a customer’s intelligence compounds over time and delivers real business outcomes.

This is what Microsoft Frontier Company was built to do: focus on end-to-end Frontier Transformation, enabling customers to amplify their IQ with AI while refining their differentiated value in the markets that they serve.

Early results demonstrate meaningful impact: Our engineers and industry experts partnered with LSEG (London Stock Exchange Group) to embed AI into LSEG Workspace, helping finance professionals ask complex questions and get quick answers across structured and unstructured financial content. The solution is underpinned by a foundation that is iteratively refined through client feedback and real-time user testing that accelerates each cycle and steadily improves model quality and scope. From LSEG to Land O’Lakes to Unilever to Novo Nordisk, our differentiated approach is already delivering measurable outcomes on our customers’ Frontier Transformation journeys.

To achieve scale, we will work closely with our partner ecosystem to extend this unique value to our customers across all markets and segments globally. We have robust FDE partnerships with our Global SI partners, including Accenture, Capgemini, EY, KPMG, PwC and others.

Central to this approach is a principle that is non-negotiable: a customer’s IQ is protected. Their data, their IP, their competitive advantage — none of it is used to train models in ways that commoditize what differentiates them in their industry. Satya put it clearly recently: there is no societal permission for an AI future that eats the intelligence of the companies it’s deployed inside. We built Microsoft Frontier Company to make sure that does not happen.

We protect that intelligence with a model-diverse, open, heterogeneous AI platform. Customers shouldn’t be locked into a single model any more than they should be locked into a single technology vendor. Microsoft’s platform gives organizations the flexibility to run the right model for each scenario — whether it comes from OpenAI, Anthropic, Microsoft AI, open source or a specialized model tuned for a specific industry — without ceding control to any one of them.

To lead this new organization, I have asked Rodrigo Kede Lima to be the President of Microsoft Frontier Company. Rodrigo brings 30 years of industry experience, and for the past six at Microsoft has led enterprise-wide transformations as a sales leader in the Americas and Asia. He has been at the forefront of helping customers and partners translate technology shifts into business outcomes, and understanding how platform innovation, engineering and partner ecosystem collaboration come together to drive growth.

I am excited about all the things that Microsoft Frontier Company will do for our customers to realize the gains of Frontier Transformation. At the end of the day, it comes down to Intelligence + Trust and empowering our customers to achieve meaningful outcomes and a return on their investments.

Learn more at www.microsoft.com/en-us/frontier-company.

Judson Althoff is the chief executive officer of Microsoft Commercial Business. He is responsible for the product strategy, sales, services, support, marketing, operations and revenue growth of the company’s commercial business, which operates in more than 120 regional and national subsidiaries globally.

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If you run or manage a small or medium-sized business, you have probably heard the phrase “AI agent” more times than you can count. Software vendors, consultants and technology platforms are all using it. Some make it sound like the next big leap forward. Others use it as a more impressive label for what is, in reality, just a chatbot.

For UK SMEs, especially those without a large internal IT team, the question is not whether AI sounds exciting. The real question is how it can be moulded to save time, reduce admin, improve customer service or help the business make better decisions without creating unnecessary risk.

This article explains the difference between AI chatbots and AI agents in plain English, why the distinction matters, and how SME owners and senior managers can build a sensible AI strategy.

AI Chatbots: The Familiar Starting Point

An AI chatbot is a tool that talks to people through text or voice. Most businesses know chatbots as website pop-ups that answer customer questions, collect contact details or point visitors towards the right page.

Traditional chatbots are usually designed around set questions and answers. They are useful when the task is predictable, such as answering opening hours, explaining a returns policy, capturing a sales enquiry or giving basic support information.

Modern AI chatbots are more flexible than older scripted bots, but they are still mainly conversational. They respond when asked. They help with information. They do not usually take ownership of a whole business process.

AI Agents: The Next Step Beyond Conversation

An AI agent is designed to do more than answer a question. It can understand a goal, work through several steps, use connected systems and complete a task with a level of autonomy.

For example, a chatbot might tell a customer how to request a quote. An AI agent could gather the information, check details against your CRM, create a draft quote, notify the right person and schedule a follow-up.

In simple terms: a chatbot talks; an AI agent acts. That does not automatically make an AI agent better. It simply means it is suited to different, usually more complex, business problems…… or, to put it another way, its about using the right tool for the right job!

AI Agents vs AI Chatbots: The Practical Difference

Should SMEs Care About AI Agents?

Yes, but with a sensible level of caution. AI agents may become highly useful for SMEs because many smaller businesses rely on manual processes, duplicated admin and key people carrying too much knowledge in their heads.

Used well, AI agents could help with repetitive work such as chasing missing information, summarising customer enquiries, preparing draft responses, routing support tickets, checking stock or service availability, and producing management summaries.

However, SMEs should not buy AI just because it is fashionable. The best starting point is not “we need an AI agent”. It is “where are we losing time, money or customer goodwill because a process is too slow, too manual or too dependent on one person?”

Where AI Chatbots Make Sense for SMEs

An AI chatbot may be the right option if your business wants to improve basic customer communication without changing internal systems too much.

• Answering common website questions
• Capturing sales enquiries outside office hours
• Helping customers find the right service page
• Reducing repetitive calls or emails to your team
• Providing simple first-line support guidance

For many SMEs, this is a practical and affordable first step. It is also easier to control because the chatbot can be limited to approved information and clear escalation routes.

Where AI Agents Could Add More Value

An AI agent becomes more relevant when a task needs several steps, judgement or interaction with business systems.

• Qualifying inbound leads and assigning them to the right person
• Preparing draft quotes from standard information
• Summarising support tickets and recommending next actions
• Checking internal knowledge bases before escalating an issue
• Creating weekly management summaries from operational data
• Following up on incomplete customer forms or missing documents

These are the areas where AI can move from “interesting tool” to “useful business assistant”. The key is to keep humans in control, especially where customer commitments, financial decisions, legal obligations or personal data are involved.

The Risks SMEs Should Not Ignore

AI agents can create real value, but they also need proper oversight. If an AI tool can access data, trigger actions or communicate with customers, it must be implemented carefully.

• Data protection: Know what information the tool can access and where that data is stored.
• Accuracy: AI can produce confident but incorrect answers, so checks are essential.
• Security: Any integration with email, CRM, finance or customer systems must be properly controlled.
• Accountability: A named person should own the process and review outcomes.
• Customer experience: Customers should be able to reach a human when needed.

For non-technical managers, the important point is simple: do not give AI more freedom than the business is ready to supervise.

A Sensible AI Starting Point for UK SMEs

Before investing in an AI chatbot or AI agent, SMEs should start with a short business review. This does not need to be complicated. It should identify where AI could support real business outcomes.

1. List the repetitive tasks that consume staff time every week.
2. Identify which tasks are low risk and rule-based.
3. Check whether the data needed is accurate, accessible and appropriate to use.
4. Decide where a human must approve the outcome.
5. Start with one small pilot rather than a business-wide rollout.
6. Measure time saved, customer response times and quality of output.

This approach helps avoid expensive experiments and keeps AI aligned with practical business value.

Why Local IT Advice Matters

For SMEs across all of the UK, the challenge is not just choosing an AI tool. It is making sure that tool fits securely into the wider IT environment.

Fruition Systems, based in Hampshire, specialises in providing a wide range of SME business IT specialisation. That means helping businesses look beyond the AI buzzwords and consider the practical foundations: secure systems, reliable data, Microsoft 365, cybersecurity, backups, access controls, support processes and staff confidence.

AI works best when the basics are already under control. If your data is disorganised, security and permissions are unclear or customer info is spread across disconnected systems, an AI project can magnify those issues rather than solve them.

So, Should Your SME Use an AI Agent or a Chatbot?

If your main issue is answering the same customer questions repeatedly, a chatbot may be enough. If your issue is a slow, repetitive internal process that crosses several systems, an AI agent may be worth exploring.

The best answer may also be both: a chatbot on the website to handle first-line enquiries, supported by carefully controlled AI automation behind the scenes.

What matters most is not the label. It is whether the solution solves a genuine business problem, protects your data and improves the way your team works.

Final Thought

AI agents are not magic….. and they are not only for large enterprises. For the right SME, used in the right way, they can remove friction, speed up admin and help people focus on higher-value work.

The businesses that benefit most will be those that start with clear goals, strong IT foundations and sensible controls. AI should support your people and processes, not replace good judgement.

Call to Action

If you are an SME owner or senior manager in Hampshire or the South of the UK and want to understand whether AI could help your business, Fruition Systems can help you review your current IT setup, identify realistic opportunities and approach AI safely and practically. Drop us an enquiry to helpdesk@fruitionsystems.co.uk and we’ll be in touch.

Speak to Fruition Systems about practical AI, automation and SME IT support. IT Helpdesk | Fruition Systems | Microsoft Cloud Services in Hampshire

FAQs:

What is the main difference between an AI chatbot and an AI agent?

• An AI chatbot mainly answers questions or guides a conversation. An AI agent can work through a task, use connected systems and take actions towards a defined goal.

Are AI agents suitable for small businesses?

• They can be, but only when there is a clear business problem to solve. SMEs should start with a controlled pilot, not a large and risky transformation project.

Do AI agents replace staff?

• In most SMEs, the better use of AI is to reduce repetitive admin and free people to focus on customer service, decision-making and higher-value work.

What should SMEs check before using AI tools?

• Check data protection, security, system access, staff responsibilities, accuracy controls and whether customers can reach a human when needed.

Is a chatbot still worth considering?

• Yes. For common questions, simple support and lead capture, a chatbot can be a cost-effective first step before considering more advanced AI agents.

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As demand for cloud and AI services continues to grow, datacenters are becoming more essential than ever. Communities also want to better understand how this infrastructure affects local resources, particularly water. At Microsoft, water stewardship has been a priority since our first datacenter builds in the early 2000s and remains a core part of our strategy today and into the future. It underpins both our Community-First AI Infrastructure initiative and our company-wide commitment to become water positive by 2030, meaning we will replenish more water than we withdraw. We are pairing our progress with continued transparency so people can understand not only how much water we use, but also how we are working to reduce that use over time.

Through continuous innovation and advancements in cooling technologies, we have improved our water use effectiveness (WUE), measured in liters per kilowatt-hour (L/kWh), by nearly 90% since our first generation of datacenters in the early 2000s. Our average WUE has decreased from 2.3 L/kWh to 0.27 L/kWh in 2025, reflecting decades of innovation and our ongoing commitment to reducing the water intensity of our datacenters while meeting the growing demand for cloud and AI services.

Across our entire owned fleet of datacenters, we are committed as a company to a 40 percent improvement in datacenter water-use intensity by 2030. As of 2025, we have reduced our water-use intensity by 25 percent, putting us well over halfway toward our goal. This strong progress reflects the impact of our continued investments in water-efficient cooling technologies, operational improvements and responsible water management practices.*

In FY25, Microsoft reached an important milestone toward its 2030 water positive commitment, replenishing more water than it withdrew across its global operations for the year. We have made this progress by decoupling datacenter growth from water use through resilient, responsible water stewardship practices and the deployment of increasingly efficient cooling technologies — demonstrating that digital growth and sustainable water management can advance together. We are committed to building on this progress and working toward sustaining water positive performance over time as we continue advancing toward our 2030 goal.

Early water stewardship by design

Beginning with some of our earliest datacenter designs, we prioritized water efficiency while minimizing impacts on energy use through the deployment of high-efficiency economizing chillers operating at elevated water temperatures. As early as 2008, we adopted direct air cooling with evaporative assist as the primary cooling approach across our datacenter fleet. This design uses significantly less electricity and up to 90% less water than traditional water-based cooling systems by relying on water only when outside temperatures exceed 85°F (29.4°C). In parts of Northern Europe, no water is required for cooling throughout the year, while in other cooler regions like Dublin and Amsterdam, water is used less than 5% of the time. In more temperate climates like Virginia, water is typically required only 10% of the year, while in the hottest climates like Phoenix, water use may increase to as much as 40% of the year. As a result, approximately 90% of our 2025 owned fleet operates using highly efficient, low- to zero-water cooling systems.

While the majority of our existing datacenters are already highly water efficient, we did not stop there. In 2024, Microsoft introduced a new datacenter design optimized for AI workloads that consumes zero water for cooling during operations, further reinforcing our commitment to water stewardship by design. This chip-level cooling solution delivers precise zonal temperature control without water evaporation by recirculating water through a closed-loop, direct-to-chip cooling system. As our datacenter fleet continues to expand, the addition of these zero-water designs will further reduce Microsoft’s water use intensity over time.

Datacenter cooling methods, explained:

• Cooling towers: Traditional systems that remove heat by evaporating water year-round.
• Hybrid fluid coolers: Evaporates water for cooling during hot summer conditions and switches to dry mode when ambient temperatures cool down.
• Direct air: Uses outside air for cooling, with little to no water use. Water is used only when outside air is above 85°F.
• Air cooled chillers: Uses mechanical refrigeration and outside air to remove heat from closed coolant loops with zero water evaporation.
• Liquid-cooled AI DCs: Uses closed-loop, direct-to-chip cooling to provide precise chip-level temperature control, removing heat efficiently with zero water evaporation.

Modernizing cooling in existing datacenters with smarter controls

Design innovation is only part of the story. We are also improving the efficiency of existing facilities that use water through a continuous focus on optimizing temperature and humidity setpoints, enabling more precise environmental control and eliminating overcooling. In addition, we regularly audit water use and compare actuals against design expectations using real-time weather data and operational analytics. This helps ensure our datacenters are performing as intended and enables us to quickly identify and address any unexpected water use. These efforts, combined with ongoing hardware and operational improvements, are all aimed at using as little water as possible.

Specifically in our Phoenix, Arizona, datacenters, implementation of these advancements led to a 23% year-over-year improvement in WUE in FY25 alone. We are now deploying these advancements across our direct-evaporatively cooled datacenters globally.

Operational improvements like these are one reason Microsoft has been able to report significant long-term reductions in water intensity across datacenter generations. They also point to the next phase of our work: expanding the use of recycled and alternative water sources wherever possible.

Leveraging recycled, reused and non-potable water

In addition to driving efficiency, we also prioritize using recycled, reused or non-potable water wherever possible in our operations. We have expanded the use of these non-potable water sources in some of our most water-intensive regions, helping reduce demand on freshwater supplies. For example, in Quincy, Washington, Singapore and San Antonio, Texas, three of our key locations for advancing water stewardship, we leverage 74%, 99% and 79% recycled, reused or non-potable water sources, respectively.

Rainwater harvesting systems are now operational at select datacenters in the Netherlands, Sweden and Ireland, with additional installations planned in Canada, the United Kingdom, Finland, Italy, South Africa and Austria. To illustrate the potential impact, Microsoft’s new datacenters in Quebec are expected to collect up to 1.5 million liters of rainwater annually, depending on local precipitation levels. This water can be used to further offset the already low water withdrawal at these sites. Expanding the use of alternative water sources in this way helps reduce pressure on municipal water supplies while supporting efficient datacenter operations.

As needed, we implement on-site water treatment systems that enable facilities to recycle water multiple times for cooling operations. These systems produce purified water suitable for reuse within cooling systems, reducing overall dependence on utility water supplies. Together, these efforts demonstrate how engineering innovation and operational excellence can work in concert to meaningfully reduce water use at the facility level.

Advancing water stewardship through investment and community partnership

We work closely with local utilities to reduce strain on community resources, and plan ahead for the sourcing and infrastructure needs associated with our operations. Beyond our operations, Microsoft’s Datacenter Community Pledge commits us to protecting local watersheds, engaging stakeholders and investing in projects that strengthen regional water resilience — helping ensure datacenter growth supports both environmental sustainability and long-term community well-being. Where system improvements are required, Microsoft funds those upgrades in full so communities do not have to shoulder the cost of supporting our operations.

Beyond our own footprint, we invest directly in community water infrastructure by modernizing water systems, expanding access, increasing reliability and helping utilities maintain stable rates and pressure. These investments create shared value for both Microsoft and the local communities we work closely with by strengthening critical infrastructure and supporting long-term water resilience. For example, near our datacenter in Leesburg, Virginia, Microsoft is funding more than $25 million in water and sewer improvements to help ensure that the cost of serving our facilities does not fall on local ratepayers. Since 2020, we have invested more than $500 million in more than 75 water and wastewater infrastructure projects that deliver meaningful community co-benefits.

Replenishment

Finally, we pair all of this work with our broader water positive commitment, our goal to replenish more water than we withdraw by 2030, while advancing our Community-First AI Infrastructure approach, which prioritizes delivering measurable benefits to the communities where we operate. This approach extends across our entire datacenter footprint, including leased facilities. In FY25, we replenished more water than we withdrew globally, marking a significant milestone in our water stewardship journey.**

We prioritize and pursue projects designed to deliver meaningful water contribution to each local community. For example, in the greater Phoenix area and nearby Nevada communities, we partner with FIDO Tech and local utilities to deploy AI-enabled leak-detection that identifies and repairs hidden breaks in aging water systems. By preventing water loss before it occurs, these efforts help keep more water in circulation, improving reliability for residents and effectively increasing the amount of usable water available across the system.

Across the Midwest, we work with The Nature Conservancy to restore historic oxbow wetlands — crescent-shaped water bodies that naturally recharge groundwater, reduce flood risk and enhance habitat for native species. These wetlands act as natural reservoirs, capturing and slowly returning water to local aquifers over time. The goal is to create more stable water availability for agriculture, healthier ecosystems and increased resilience for nearby communities throughout the year.

Looking ahead

As water challenges become increasingly complex around the world, Microsoft remains deeply committed to protecting water as a vital natural resource. We continue to advance datacenter innovations that reduce water use intensity while supporting the growing performance demands of cloud and AI services. Through zero-water cooling designs optimized for AI workloads, water reuse initiatives both on and off our campuses and community-focused stewardship programs, we are working toward a future where digital growth and responsible water management go hand in hand.

We are also exploring zonal cooling architectures that more precisely align cooling approaches with the needs of different hardware types, improving efficiency while supporting a diverse mix of AI and traditional workloads.

Datacenters are essential infrastructure for the digital economy, and we believe they should be built and operated in ways that benefit the communities they serve. Over the last decade, we have demonstrated that technological advancement and environmental stewardship can progress together, and we remain committed to continuing that journey as we build the datacenters of the future.

Top image caption: Aerial view of Microsoft datacenter campus in Wisconsin.

Judy Priest leads technology strategy, innovation and research for Microsoft’s global cloud and AI infrastructure, driving advances in datacenter architecture, sustainability, power, cooling, energy and emerging technologies that enable reliable, scalable services.

Steve Solomon is a professional engineer leading the engineering strategy behind the company’s global cloud and AI infrastructure. He specializes in datacenter design, sustainability, power and cooling innovation, helping advance reliable, efficient and community-focused infrastructure at hyperscale.

*Footnote 1: Measured as water withdrawals per megawatt (MW); based on a 2022 baseline.

**Footnote 2: To understand how Microsoft calculates and tracks water replenishment data, please refer to our FY 2024 Environmental Data Fact Sheet.

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Cloud operations are entering a new era as AI-driven and autonomous agents become a larger part of modern software systems. As software becomes increasingly agentic, the challenge is no longer just managing greater scale and complexity. Operators must also contend with systems that evolve faster, act more autonomously and interact across an expanding network of dependencies.

As applications, models, APIs and infrastructure become increasingly interconnected, their behavior is harder to understand end to end. Systems no longer fail in isolation. They fail through interactions across dependencies, services and environments that are constantly changing in real time.

To help organizations operate effectively in these increasingly dynamic environments, today we’re announcing the general availability of the Azure Copilot Observability Agent. Built on Microsoft Azure Monitor, it correlates signals across agents, applications, infrastructure and services to provide the context needed to operate confidently in this new environment.

Observability becomes foundational in an agentic world

In a recent survey of 250 IT decision-makers, Microsoft and Material found that 84% of organizations report increased cloud complexity, with 69% saying it is outpacing their current operating model. The impact is most acute across security, cost management and performance, and it extends across the entire operations lifecycle.

As the pace and scale of change accelerate, no individual or team can realistically maintain the full context required to diagnose and resolve issues quickly enough. This is driving a shift toward agentic operations, where intelligence augments how systems are understood and managed.

Observability is foundational to this shift. It provides the real-time understanding of system behavior that agents depend on to reason, adapt and act. Without a connected view across signals, even the most advanced agents lack the context required to operate reliably.

From signals to resolution with the Observability Agent

We designed the Observability Agent to help operators move more quickly from detection to understanding. It connects logs, metrics, traces, topology and operational context across environments, reducing the time it takes to identify the root cause of an issue.

As telemetry spreads across systems, operators are often forced to piece together context across multiple tools. The Observability Agent addresses this fragmentation by reasoning across signals in real time and unifying that context into a single operational view. These agentic capabilities are integrated directly into existing workflows, helping teams move from investigation to resolution faster with clear, actionable insight.

We’re already seeing customers use the Observability Agent to reduce manual effort, accelerate incident resolution and improve operational clarity:

“The biggest value is speed! The [Azure Copilot] Observability Agent helps us resolve incidents faster and reduce operational overhead by turning logs, metrics and traces into plain English insights. These agents run deep investigations and provide remediation recommendations almost immediately, compared to hours or even days previously.

Since adopting these capabilities, we’ve reclaimed an estimated 250 engineering hours monthly that are now redirected toward supporting new applications and features. We can use natural language to detect, diagnose and remediate issues faster than ever before.”

— Narmada Krishnaswamy, Head of KPMG Audit Application Support and Operations

“Azure Copilot Observability Agent helped us move from manual incident hunting to faster, AI-guided investigations. For PolicyVault, it pulls together the telemetry from our service, correlates it with Azure resource health and gives us actionable next steps based on the investigation. That means we’re not just seeing what broke; we’re getting a much clearer idea of why it happened and what to do about it, which saves us a lot of time during incidents.”
— Vladimir Gusarov, Founder & CEO, PolicyVault

“Azure Copilot’s Observability Agent helps us move faster from signal to insight. By bringing together our telemetry and guiding us toward likely root causes, it reduces the time and effort needed to investigate incidents and keeps our teams focused on what matters most.”
— Theus Hossmann, Chief Technology Officer at Ontinue

Beyond improving incident response, this shift reflects a new approach to cloud operations, where systems can continuously reason across signals and act on that understanding.

Check out our Tech Community blog post to learn more about the Azure Copilot Observability Agent.

From observability to agentic operations across the cloud lifecycle

Observability is part of a broader shift to agentic operations. As systems become more autonomous, operations expand from understanding what is happening in production to continuously improving how those systems behave over time.

In an agentic model, this forms a lifecycle. Systems generate signals, agents interpret those signals, take action and learn from outcomes. Over time, this creates a feedback loop where each operational cycle improves the next, increasing system resilience and efficiency.

This shift requires more than better visibility. It requires a coordinated approach across the lifecycle, from observability and diagnosis to optimization and remediation where insight and action are tightly connected.

As agents take on a greater role in that lifecycle, governance becomes central to how systems are trusted and controlled. Policy, auditability and guardrails ensure that actions taken by agents align with organizational intent and operate within defined boundaries. Human oversight remains essential, not as a bottleneck, but as a mechanism for building confidence and ensuring reliability as automation scales.

This is where Azure is uniquely positioned. By bringing together observability, automation and governance within a connected platform, Azure enables organizations to move from isolated tools to an integrated operational model that spans the full lifecycle.

Azure Copilot Observability Agent plays a key role in this model by grounding agentic systems in real-time operational context. As organizations build and deploy more agents, this foundation becomes critical for ensuring those systems operate effectively and responsibly.

Cloud operations are shifting from reactive management to a continuous, agent-driven lifecycle of learning, adaptation and control. This vision of agentic cloud operations is already taking shape across Azure. Read our companion Azure Blog post for more details.

Brendan Burns is a co-founder of the Kubernetes open source project and corporate vice president for Azure cloud-native open source and the Azure management platform including Azure Arc. He is also the author and co-author of several books on Kubernetes and distributed systems.

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