My job is to help you turn unmanaged, inconsistent AI adoption into a governed workforce capability that improves productivity, reduces operational drag and delivers measurable results without enterprise complexity or consultancy overhead.
I help organisations figure out what AI can, and should, do for them, and then make it happen. Over 17 years I have scoped, designed and led more than 30 AI deployments across healthcare, defence, financial services, government and global enterprise. Not pilots or proofs of concept that go nowhere, but working systems that reduce workload, improve outcomes and generate measurable results.
Before this I built and sold two technology businesses. I founded ubisend, a conversational AI platform, scaled it from zero to acquisition in 2022, and before that built and exited a FinTech business in 2014. Building both sides of the table gives a perspective that is genuinely uncommon in consultancy: I understand the commercial reality of running a business where delivery quality, responsiveness and client relationships directly impact revenue, and I understand what it takes to build something that actually works under real operating conditions.
I started dkww because UK SMEs are now dealing with exactly the operational pressures larger organisations faced years ago: staff using AI informally without governance, high-value people buried in repetitive admin and leadership under pressure to improve productivity without endlessly growing headcount. The difference is that SMEs rarely have the internal capability, budget or time to navigate it alone.
My goal with you is to bring the deployment depth, commercial realism and implementation discipline from my background in a way that is practically delivered and designed to build internal capability rather than consultancy dependency.
Founder-led AI workforce enablement consultancy focused exclusively on UK SMEs. Practical implementation across recruitment, accountancy, legal and professional services. Workforce enablement, workflow redesign, governance and embedded fractional operating support.
Led global AI scoping, adoption and delivery following ubisend's acquisition. Responsible for enterprise AI deployments across healthcare, defence, public sector and global enterprise clients including the NHS, BAE Systems, MSD and Johnson & Johnson.
Founded and scaled ubisend from startup to acquisition. Built a conversational AI platform serving clients from UK SMEs to global enterprises. Delivered 30+ AI deployments across regulated, commercially sensitive and high-volume operational environments before the platform was acquired in March 2022.
Joined as CTO to bring technical rigour to a team working on behaviour change at scale across governments, NGOs and global brands. Built early experience in how technology influences operational decision-making, which proved directly transferable to AI adoption work.
Founded and scaled a FinTech startup focused on algorithmic and discretionary FX trading. Built proprietary trading infrastructure, automation systems and a structured education programme for retail traders. Acquired 2014.
First in class at RAF College Cranwell. Eight years as a fast jet pilot including operational tours before transitioning to technology and business.
Deploying AI into a business without first understanding how the workforce uses it, where the gaps are and what governance is in place produces faster versions of the same problems. The right sequence is always workforce visibility, then workflow improvement, then embedded operational support.
In most SMEs, AI adoption has already started informally. Staff are using tools without policy, consistency or oversight. The first job is always to understand what is actually happening before designing anything new.
Workflows, governance and AI capabilities should ultimately be owned and operated internally by the business. The goal is a team that uses AI confidently and consistently, not a team that depends on an external consultant to function.
Not every workflow benefits from AI. Not every team is ready for it. Part of my role is identifying where structured enablement will genuinely improve commercial outcomes and where it will not. Honest assessment before implementation.
Unmanaged AI adoption creates data risk, compliance exposure and inconsistent output. Practical governance, appropriate to SME scale, is a core part of every engagement, not an afterthought bolted on at the end.
I have built two businesses from nothing and delivered AI into some of the most complex operational environments in the world. SMEs don't need a smaller version of enterprise consultancy. They need someone who has done the real work and will do it again for them, at their scale.
The operational patterns below are drawn from real-world AI deployments across regulated, high-volume and commercially sensitive environments. See full engagements.
Conversational AI pre-screening across 10 to 15 structured topics. 73% reduction in unqualified applications reaching the recruitment team.
AI-driven concierge integrated with appointment automation, treatment guidance and measurable reduction in missed appointments.
HR AI assistant serving 100,000 employees across 75 countries. 43% reduction in central inbox traffic within a three-month proof of concept.
High-trust AI deployments handling over 80% of incoming citizen enquiries across housing, council tax, planning and local services.
AI HR assistant deployed across four countries in English, Dutch and German. Fewer than 13 escalations to human agents over 12 months.
High-volume WhatsApp and SMS AI-triage integrated with Reed and Indeed APIs. 30 to 50 screening calls per week eliminated, candidates directly into ATS.
Searchable institutional knowledge powering faster proposal drafting and more consistent client delivery across distributed teams.
AI-driven customer engagement reducing support tickets by 48% within the first 14 days of deployment across a global enterprise client base.