DAN WILLIAMS, Professional Services at Microsoft

We speak to Dan Williams, Director of Industry Strategy at Microsoft,whose work focuses on transforming how organisations deliver value through intelligent technologies. From legal and consulting firms to accounting and advisory services, the professional services sector is under increasing pressure to innovate—and AI is at the heart of that transformation.

Your Tech Industry Journey

I’ve spent over a decade in the tech industry, and if I had to sum up the journey, it’s been all about evolving from someone who’s deep in the tech to someone who uses that knowledge to drive real business impact.

I started in technical and pre-sales roles—building solutions, solving complex problems, and translating business needs into tech outcomes. One of the standout chapters in that journey was serving as CTO for Microsoft’s UK aviation business. Working with some of the most operationally complex and safety-critical organisations in the world gave me a deep appreciation for the role technology plays not just in transformation, but in resilience and precision.

Over time, I realised I wanted to have a bigger seat at the table—to influence direction, not just execution. Stepping into a sales role at Microsoft was a turning point. It gave me the chance to lead transformation conversations across the wider professional services space, helping organisations rethink how they operate, compete, and grow in an AI-first world.

Now, my role blends commercial ownership with technical depth. I’m trusted by senior leaders to help them navigate AI, cloud, and security—not just as tech buzzwords, but as practical enablers of change. It’s that mix of strategic thinking and grounded execution that defines how I work.

AI in Professional Services

AI is completely shaking up the professional services world. It’s automating the boring, repetitive stuff—things like invoice processing, document review, onboarding—and freeing people up to focus on what really adds value: insight, relationships, strategy.

In finance, AI is streamlining everything from accounts payable to forecasting. We’re seeing tools that can reconcile transactions in seconds, surface anomalies before they snowball, and even generate predictive models to inform decision-making. That’s powerful in any business, but in services—where time really is money—it’s a game changer.

In HR, AI is transforming how firms attract and manage talent. It can rewrite job descriptions to remove bias, suggest high-potential candidates based on more than just keywords, and act as a 24/7 assistant for new joiners—answering policy questions, flagging missed tasks, and speeding up time to productivity. For firms constantly competing for top talent, that edge really matters. And in areas like tax and audit, where the volume of documentation is huge and the margin for error is tiny, AI is already driving massive efficiency gains. Instead of manually reviewing hundreds of documents, teams are using AI to surface outliers, summarise trends, and even generate draft commentary that’s then reviewed and fine-tuned by a human expert. The end result? Faster delivery, greater consistency, and higher confidence in the output.

But this isn’t just about automation. What we’re really seeing is a shift in the operating model. AI is helping firms move from reactive service delivery to proactive insight. Rather than just reporting on what’s happened, teams can advise clients on what’s coming—armed with real-time data, predictive analytics, and intelligent context. That flips the value proposition from compliance to strategic partnership.

For many firms, AI is also levelling the playing field. Mid-sized consultancies or niche players can now punch well above their weight by leveraging AI to scale capabilities, personalise services, and respond to clients faster than ever before. We’re still early in the curve, but the direction of travel is clear: AI isn’t just optimising existing processes—it’s unlocking entirely new ways of working that are leaner, smarter, and far more client-centric.

Microsoft 365 Copilot & Intelligent Automation

Copilot is a game changer because it doesn’t require you to learn a new tool—it plugs straight into the apps you already live in: Outlook, Word, Excel, Teams.

For professional services firms, where time and accuracy are everything, this is massive. Picture someone in finance asking Copilot to pull key metrics into a client report, or a consultant summarising notes from a Teams call and turning them into a client-ready proposal—all in minutes.

This kind of intelligent automation is especially powerful when you think about the pressure consultants are under. They're often only able to bill 8 hours a day, yet the workload routinely stretches to 12–14 hours. There’s a gap between what’s expected and what’s sustainable—and AI can help bridge it.

And at its core, that’s what makes Copilot so important. It’s not just a tool—it is the UI for AI. It’s how people access the power of large language models without needing to understand how they work. That shift—from complicated tech to conversational experiences—makes AI truly accessible at scale.

It’s like giving every employee their own digital assistant. You’re not just working faster—you’re making better decisions, reducing manual effort, and creating space for the kind of work that actually energises people.

The Rise of Agentic AI& Microsoft Agents

Agentic AI is about giving AI the ability to go beyond answering questions—it can now reason, decide, and act on your behalf within set guardrails. Unlike traditional automation, which is rigid and rule-based, Agentic AI operates more like a digital colleague that understands your objectives, adapts to your context, and executes tasks with autonomy.

The real shift here is that you’re no longer telling the system what steps to take. Instead, you’re defining an outcome—like “prepare a project risk summary”—and the AI agent figures out how to get there. It might pull data from different systems, interpret documents, send reminders, or escalate decisions. It’s orchestration, not just execution.

In professional services, this is huge. Workflows are fragmented across emails, spreadsheets, and legacy systems. Coordinating that manually eats up time and mental bandwidth. Agentic AI dynamically stitches those workflows together in real-time.

It’s also context-aware. Agents don’t just complete tasks—they understand your organisation’s language, your past interactions, even who owns what. That enables smarter decision-making and reduces friction in everyday work. “AI won’t replace the consultant—it’ll elevate their impact.”

Critically, Agentic AI also introduces continuity. When people go on holiday, leave a firm, or simply switch roles, knowledge and process ownership often disappears with them. Agents can provide continuity of execution and awareness across projects, teams, and even departments—something no traditional system or workflow tool can replicate.

We’re just scratching the surface, but what’s clear is this: Agentic AI won’t just make individuals more productive—it’s going to fundamentally rewire how companies operate. It allows businesses to scale decision-making and action-taking in a way that’s never been possible before, while still keeping humans in control of the strategy and governance.

Overcoming AI Adoption Challenges

For all the excitement around AI, the reality is that adoption in professional services is often slower and more complex than people expect. There’s plenty of ambition, but turning that ambition into something operationally meaningful is where the real friction lies.

The biggest issue I see is organisational readiness—and that’s not just about technology. It’s cultural. It’s structural. It’s human. Many firms are still operating with legacy mindsets and fragmented data estates that simply weren’t designed to support intelligent systems. There’s a belief that AI will fix inefficiencies—but in truth, AI shines a spotlight on them. If your workflows are unclear or your data is all over the place, AI won’t solve that—it’ll surface the pain.

Then there’s the trust gap. In a sector built on reputation, accuracy, and compliance, many professionals are understandably cautious about handing over too much control to AI—especially when it comes to client work. There’s a fear that the tech will make mistakes, or worse, erode the human value proposition. That’s a legitimate concern—but one that can be addressed with transparency, education, and responsible AI practices baked in from day one.

Change fatigue is another factor. Many firms have gone through wave after wave of digital transformation projects that never fully landed. So when AI comes along, it can feel like just another shiny initiative. The challenge is to ground it in reality—not big-picture “transformation” language, but practical, value-led use cases that make someone’s Monday morning easier.

Here’s a real-world example. I worked with a professional services firm that wanted to deploy AI to streamline its proposal process. On paper, it was a quick win—use AI to summarise meeting notes, surface relevant case studies, and auto-generate the first draft of a pitch deck. But when we dug in, we found that content was stored in inconsistent formats, spread across different systems, and often out of date. The proposal teams also had no single owner of the process end-to-end. So before we could talk AI, we had to help them clean up their content, define ownership, and rethink their knowledge workflows. Once that foundation was in place, the AI piece slotted in smoothly—and the results were immediate: faster proposals, higher win rates, and happier consultants.

One of the approaches I’ve seen work well is shifting from a tech-led to a business-led AI strategy. That means starting with problems, not platforms. We look at high-friction processes—manual reporting, compliance reviews, proposal generation—and design AI use cases that solve real pain points. From there, we focus on pilots that prove value quickly and build internal momentum.

Just as importantly, I always recommend firms invest in AI fluency across the business. That doesn’t mean everyone needs to become a data scientist. But they do need to understand what AI can (and can’t) do, how it affects their role, and where their judgment is still critical. AI isn’t replacing people—it’s reshaping what people are responsible for.

And finally, we can’t ignore the ethical dimension. Professional services firms operate in regulated, client-sensitive environments. Any AI deployment must be responsible by design—aligned with data privacy, fairness, and transparency principles. If that foundation isn’t in place, the trust just won’t be there.

The good news? Once firms get past the initial blockers, the flywheel starts to turn fast. Confidence builds, use cases expand, and AI becomes not just another IT project—but a strategic asset woven into how the firm delivers value, inside and out.

The Future of AI & Professional Services

The AI we’re seeing today—Copilot, automation, intelligent workflows—is just the beginning. Over the next 5, 10, 15 years, we’ll see deeper shifts that don’t just enhance how firms operate—they’ll fundamentally reshape what professional services look like.

In the next 5 years, AI will move from being a productivity tool to an embedded part of delivery models. We’ll see firms deploying internal AI agents that operate like digital team members—monitoring workflows, drafting outputs, surfacing insights—freeing up human consultants to focus on strategic thinking and relationship building. AI won’t replace the consultant—it’ll elevate their impact.

We’ll also see the rise of firm-specific foundation models. These are AI models trained on a firm’s own intellectual property—case studies, methodologies, playbooks—so they can deliver advice and outputs that reflect the firm’s unique thinking and tone. That’s not commoditisation—it’s amplification. It ensures firms can deliver value faster and more consistently, without losing what makes them distinctive.

By 10 years, traditional commercial models may come under pressure. If AI enables work to be delivered faster and more efficiently, clients will expect pricing to reflect outcomes rather than time spent. That doesn’t devalue expertise—it puts a premium on it. Advisory services will be judged less by how long they take and more by the quality of insight they deliver.

New types of firms could also emerge—AI-native, agile, and global from day one. But established firms have a huge advantage: trust, reputation, and deep client relationships. The opportunity is to combine those strengths with AI-native thinking—rethinking how value is delivered and where human expertise adds the most weight.

Looking 15 years ahead, we may see clients using AI tools that mirror the logic and IP of their advisors. But this isn’t about disintermediation—it’s about deepening relationships. Imagine clients having access to their own secure, always-on advisory assistants that are powered by your firm’s thinking, trained collaboratively, and constantly learning. That could actually increase reliance on the firm—not reduce it—because the AI is only as good as the expertise it’s built on.

What’s clear is that the nature of work will evolve. AI will change the pace, the expectations, and the way services are delivered—but the human layer will remain critical. Trust, empathy, judgment, and creativity will become even more valuable, not less. The firms that lean into this change—thoughtfully, strategically, and with their people at the centre—will be the ones that lead the next era of professional services.

Your Advice for Business Leaders

If you’re leading a professional services firm and looking to make AI part of your growth story—not just a short-term efficiency play—here are a few principles I’d recommend:

Anchor everything in real problems. Start with use cases that matter to your people and clients—don’t chase trends, chase impact.

Design for scale from day one. Don’t treat AI as a series of pilots. Build a clear, strategic roadmap that connects today’s experiments with tomorrow’s operating model.

Focus on firm-specific intelligence. Your IP is your edge. Make sure your AI reflects your voice, your logic, and your standards—not just generic insights. Invest in AI fluency, not just tools. It’s not about training everyone to prompt perfectly—it’s about building confidence, clarity, and culture around how AI is used.

Build trust with responsible AI. Governance, transparency, and ethics aren’t side considerations—they’re the foundation for sustainable adoption.

Lead the change, don’t just manage it. AI is not a productivity tool—it’s a leadership moment. The firms that embrace that mindset will pull ahead.