From Pilots to Production: Getting Agentic AI Deployment Right
We are entering a new phase of AI adoption. Not the era of pilots, proofs of concept, or cautious experimentation, but the age of deployment. AI systems that can reason, plan and act are no longer experimental, they're being deployed across real business workflows right now.
For UK businesses, this presents both a major opportunity and a significant challenge. All sectors can drive commercial gain, but those such as as financial services, healthcare, professional services and the public sector stand to benefit enormously from Agentic AI. These are industries where complexity, administrative burden and process inefficiency create significant opportunities for AI to augment teams, automate workflows and improve responsiveness.
In financial services, that may mean AI agents helping automate onboarding, compliance monitoring or customer servicing processes. Across the public sector, there is an opportunity to reduce friction in citizen services and free employees from manual processes. The common thread is not replacing people, but removing operational complexity.
However, these are also sectors operating under increasing pressure around regulation, data quality and technology dependency. As organisations begin introducing AI systems capable of taking action rather than simply generating insight, these challenge become far more significant.
Getting Agentic AI right requires organisations to address all three.
The landscape: uncertainty is the operating condition
UK technology leaders are making Agentic AI decisions against a backdrop of considerable uncertainty. Geopolitical shifts are reshaping technology supply chains. Cloud infrastructure remains heavily concentrated among a small number of providers. Boards are increasingly askIng questions around resilience, control and long-term dependency. And the economics of AI, currently characterised by aggressively priced access to frontier models, will not stay as they are.
Recent research from Zoho's Digital Health Study suggests that many organisations may still be building AI ambitions on unstable foundations. While AI enthusiasm remains high, only 35% of UK businesses responding to the survey have strong digital health foundations. More significantly, businesses with strong digital health are 43 times more likely to see AI as critical to business success than organisations with poor digital health.
The organisations thinking carefully about Agentic AI deployment are not just asking what this technology can do. They are asking broader questions: How dependent are we becoming? What happens if supplier relationships change? And who ultimately controls the intelligence layer within our organisation? These are not reasons to delay adoption. They are reasons to adopt using a very considered intentional strategy.
The challenges: what is actually blocking deployment
As organisations move from AI pilots to production environments, similar barriers repeatedly emerge.
The first is data quality. Agentic systems do not just retrieve information; they act on it. They trigger workflows, make decisions, and increasingly interact with systems on behalf of users. The quality of those actions depends entirely on the quality of the data beneath them. Data quality has become a prerequisite for AI deployment, not a nice-to-have but a foundation. Siloed and Fragmented data can create hindrances to AI deployment. That argument applies with even more force to Agentic AI. A poorly calibrated recommendation is recoverable. An agent that acts on poor data is not.
The second blocker is compliance complexity. UK GDPR, evolving ICO guidance, and the downstream implications of regulations such as the EU AI Act create a landscape that can be difficult to navigate, particularly for organisations operating across multiple regions or highly regulated industries.
The third, and perhaps most underestimated, challenge is employee trust. Unlike previous generations of AI, Agentic systems are highly visible because they take action. Employee who do no understand what systems are doing, or why decisions are being made, will quickly lose confidence in them.
We are already seeing practical examples of organisations taking a measured approach. UK technology provider SysGroup has pursued an AI-first strategy within customer service operations, using embedded AI capabilities to generate initial responses, surface customer sentiment and support employees directly in workflows. Rather than attempting immediate full autonomy, AI has been introduced to augment teams while maintaining human oversight.
There is an important lesson in that approach: successful adoption rarely begins with replacing people. More often, it starts with trusted data, focused use cases and gradual implementation that builds confidence before autonomy expands.
The solutions: technical, organisational and policy levers
Scaling responsibly means moving beyond isolated AI experiments and embedding governance, oversight and trust into deployment from the outset.
On the technical side, the foundation has to be right before the agents are built. That means investing in data governance before AI architecture, and making deliberate choices about the models and infrastructure those agents will run on. There is a strong case for right-sized models: smaller and more specialised models operating with rich contextual data, over large frontier models for most enterprise workflows.
On the organisational side, the most successful deployments treat Agentic AI as a change management programme rather than simply a technology rollout. Human oversight, accountability, and phased implementation are not barriers to innovation. They are what make innovation sustainable.
On the policy side, the UK has an opportunity to set a standard around responsible AI deployment. Greater clarity around implementation in regulated sectors would materially reduce uncertainty and support broader adoption.
Boards are also beginning to ask broader questions about resilience and control. This shift is already visible in procurement decisions, with 87% of UK organisations saying data sovereignty is now an important or essential factor when selecting technology platforms, according to Zoho's Digital Health Study.
Data sovereignty is no longer simply a compliance issue. Increasingly it is becoming a strategic one.
Sachin Agrawal
Managing Director, Zoho UK
Sachin Agrawal
Managing Director, Zoho UK
Sachin Agrawal is the Managing Director of Zoho UK. Zoho is global software product company with 900,000 customers in 150 companies. It has a large porfolio of products such as Zoho CRM, Zoho Desk and Zoho Workplace, covering all functional areas such as sales, marketing support, finance, IT and collaboration. Prior to his current role, Sachin managed a few of Zoho’s product lines globally and the account management team. Before Zoho, Sachin was an entrepreneur for five years and built an HR Tech SaaS business. Earlier he spent 16 years in consulting, restructuring and enterprise technology space with companies such as IBM, A&M, Tech Mahindra & Tata Group. During this period he worked across various regions including India, APAC, Middle East & Americas.
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Read our guest blog from Sachin Agrawal, Managing Director of Zoho UK, discussing how AI has moved beyond pilots, proofs, and experimentation, and is now firmly in the deployment stage.
Derek Thompson, Senior Vice President and GM, EMEA at Workato, shares his insights on how agentic AI is at risk of becoming a 'side project' for many, without intelligent and ambitious enterprise integration.
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Kir Nuthi
Head of AI and Data, techUK
Kir Nuthi
Head of AI and Data, techUK
Kir Nuthi is the Head of AI and Data at techUK.
She holds over seven years of Government Affairs and Tech Policy experience in the US and UK. Kir previously headed up the regulatory portfolio at a UK advocacy group for tech startups and held various public affairs in US tech policy. All involved policy research and campaigns on competition, artificial intelligence, access to data, and pro-innovation regulation.
Kir has an MSc in International Public Policy from University College London and a BA in both Political Science (International Relations) and Economics from the University of California San Diego.
Outside of techUK, you are likely to find her attempting studies at art galleries, attempting an elusive headstand at yoga, mending and binding books, or chasing her dog Maya around South London's many parks.
Usman joined techUK in January 2024 as Programme Manager for Artificial Intelligence.
He leads techUK’s AI Adoption programme, supporting members of all sizes and sectors in adopting AI at scale. His work involves identifying barriers to adoption, exploring solutions, and helping to unlock AI’s transformative potential, particularly its benefits for people, the economy, society, and the planet. He is also committed to advancing the UK’s AI sector and ensuring the UK remains a global leader in AI by working closely with techUK members, the UK Government, regulators, and devolved and local authorities.
Since joining techUK, Usman has delivered a regular drumbeat of activity to engage members and advance techUK's AI programme. This has included two campaign weeks, the creation of the AI Adoption Hub (now the AI Hub), the AI Leader's Event Series, the Putting AI into Action webinar series and the Industrial AI sprint campaign.
Before joining techUK, Usman worked as a policy, regulatory and government/public affairs professional in the advertising sector. He has also worked in sales, marketing, and FinTech.
Usman holds an MSc from the London School of Economics and Political Science (LSE), a GDL and LLB from BPP Law School, and a BA from Queen Mary University of London.
When he isn’t working, Usman enjoys spending time with his family and friends. He also has a keen interest in running, reading and travelling.
Sue leads techUK's Technology and Innovation work. This includes work programmes on AI, Cloud, Data, Quantum, Semiconductors, Digital ID and Digital ethics as well as emerging and transformative technologies and innovation policy. In 2025, Sue was honoured with an Order of the British Empire (OBE) for services to the Technology Industry in the New Year Honours List. She has also been recognised as one of the most influential people in UK tech by Computer Weekly's UKtech50 Longlist and was inducted into the Computer Weekly Most Influential Women in UK Tech Hall of Fame.
A key influencer in driving forward the tech agenda in the UK, in December 2025 Sue was appointed to the UK Government’s Women in Tech Taskforce by the Technology Secretary of State. She also sits on the UK Government’s Smart Data Council, Satellite Applications Catapult Advisory Group, Bank of England’s AI Consortium and BSI’s Digital Strategic Advisory Group. Previously, Sue was a member of the Independent Future of Compute Review and co-chaired the National Data Strategy Forum. As well as being recognised in the UK's Big Data 100 and the Global Top 100 Data Visionaries in 2020, Sue has been shortlisted for the Milton Keynes Women Leaders Awards and has been a judge for the Loebner Prize in AI, the UK Tech 50 and annual UK Cloud Awards. She is a regular industry speaker on issues including AI ethics, data protection and cyber security.
Prior to joining techUK in January 2015, Sue was responsible for Symantec's Government Relations in the UK and Ireland. Before that, Sue was senior policy advisor at the Confederation of British Industry (CBI). Sue has an BA degree on History and American Studies from Leeds University and a Master’s Degree in International Relations and Diplomacy from the University of Birmingham. Sue is a keen sportswoman and in 2016 achieved a lifelong ambition to swim the English Channel.
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