Life at Microsoft: Trust, AI and ERP with Claire Purdue

What does it actually take to move into AI with confidence?

In this episode of The Catch Up Podcast, host Phillip Blackmore speaks with Claire Purdue, Senior Solutions Engineer at Microsoft, about her non-linear route into technology and how the pre-sales role has changed in the era of Dynamics 365 and Copilot. Claire explains why customers no longer ask what a system can do, but how they can work differently, safely and responsibly, and why the answer starts with data foundations rather than a bolt-on.

With AI adoption among UK small and medium sized businesses rising from 35 per cent in 2025 to 54 per cent in 2026, according to the British Chambers of Commerce, the pressure to act is real, and so is the risk of acting without governance.

From reading body language on a Teams call to setting guardrails, auditability and ownership around AI, this conversation makes the case that as technology absorbs the repetitive work, the human side of the job matters more, not less.

• (00:00) - Welcome to The Catch Up Podcast
• (02:16) - A Non-Linear Route into Technology
• (06:06) - Canada, CRM and Joining Microsoft
• (08:16) - The Skills Behind Great Pre-Sales
• (12:10) - Why It Is Okay to Say I Do Not Know
• (14:56) - Relatability as the Core Pre-Sales Trait
• (24:23) - Discovery, Boundaries and Reading the Room
• (30:14) - How AI Has Reshaped the Solutions Role
• (34:42) - Handling Sceptical Executives on AI
• (41:13) - Trust, Guardrails and AI Governance
• (45:06) - Data Foundations Before AI
• (52:48) - Bring Your Team with You

Claire Purdue: Claire Purdue is a Senior Solutions Engineer at Microsoft in the UK, working with customers across Microsoft Dynamics 365 and the wider Copilot and AI portfolio. Her route into technology was deliberately non-linear: a degree in maths, statistics and computing, a first job in software support, a move into consultancy, self-taught PRINCE2 study that took her into project management, and then a step into account management as the first account manager her software vendor ever hired. She moved into pre-sales, spent two years working on a construction CRM system in Canada, and joined Microsoft as a technical specialist on her return to the UK. She holds the MB-310 Microsoft Dynamics 365 Finance certification along with Microsoft Business Value Management Practitioner and Mentor recognitions, and has featured in Microsoft's My #MicrosoftLife series talking about life inside the Business Applications team. Her focus today is helping organisations move to AI with clear guardrails, strong data foundations and confident, human led change.

Episode Insights:

• Careers in the Microsoft ecosystem are rarely linear, and experience in support, consultancy and project management is exactly what makes a strong pre-sales professional.
• Saying you do not know, then following up, builds more trust than an answer invented on the spot, and credibility is the whole product in a pre-sales conversation.
• Relatability is the one trait every effective pre-sales professional shares, because customers remember the person who presented long after they forget the feature list.
• The buying question has shifted from show me what your system can do to how can we work differently, safely and responsibly, which makes AI readiness a strategy conversation rather than a demo.
• AI still needs ownership, usage boundaries and auditability, and it cannot compensate for poor data, so governance and data foundations come before capability.

Action Points:

1. Audit your data before you buy anything: Ask your team to review duplicates, structure and reporting quality in your current system of record. Treat a migration or AI project as the moment to clean house rather than a reason to lift and shift. Poor inputs will produce poor outputs no matter how capable the technology is.
2. Name the tasks you want to remove: Ask each team to identify the repetitive, manual work they dislike most. Use those tasks as the first AI use cases so value is visible quickly and scepticism has somewhere concrete to land. This turns an abstract AI strategy into a short list of measurable wins.
3. Set your guardrails early: Define usage boundaries, approval steps and auditability before you widen AI access across the business. Seventy-eight per cent of executives lack strong confidence they could pass an independent AI governance audit within 90 days, according to Grant Thornton's 2026 AI Impact Survey. Write the rules down while the estate is still small.
4. Treat output validation as a skill: Build the habit of checking AI output rather than accepting it. Microsoft's 2026 Work Trend Index found that 86 per cent of AI users treat output as a starting point rather than a final answer. Make that expectation explicit in your team's ways of working.
5. Bring your whole team with you: Do not confine a transformation programme to the C-suite or the project team. Put change management in place early, involve the people who will use the system daily and give them a say in decisions. Nobody likes being told what to do, and engagement is what turns a go-live into adoption.

The Catch Up Podcast brings you candid conversations with industry leaders, consultants, and change-makers from the Microsoft Dynamics and tech ecosystem. Hosted by Phillip Blackmore, Sales Director at Catch Resource Management, each episode dives into the real stories behind business transformation, career pivots, and scaling success. Expect thoughtful interviews, practical insights, and honest reflections.

Brought to you by Catch Resource Management, a leading UK recruitment specialist for Microsoft Dynamics and ERP talent, this podcast is your inside track to the people shaping the future of enterprise technology. Tune in for new episodes and stay ahead of the curve.

The Catch Up Podcast is produced by Story Ninety-Four in Oxford, UK.