Publication date: June 2, 2026
We are pleased to announce that KG Legal Kiełtyka Gładkowski contributes to techUK’s annual Tech & Innovation Focus Week, taking place from 15–19 June 2026. The initiative brings together industry leaders, technology experts and innovators to discuss the transformative technologies shaping the future of the UK economy.
LINK: https://www.techuk.org/resource/call-for-contributions-techuk-s-2026-tech-innovation-focus-week.html
For this year’s focus week, we submitted a contribution under the Agentic AI theme, exploring both the opportunities and challenges associated with the deployment of increasingly autonomous AI systems across public and private sectors.
Drawing on our experience at the intersection of technology, law and regulatory compliance, our article examines how organisations can move beyond experimentation and implement AI agents in a practical, secure and accountable manner. Particular attention is given to the role of Agentic AI in the public sector, where intelligent automation has the potential to improve administrative efficiency, service delivery and decision-support processes.
The article goes beyond the discussion of technological capabilities alone. It highlights the legal and governance frameworks that are essential for responsible AI adoption, including UK GDPR compliance, AI governance structures, accountability mechanisms and regulatory obligations that organisations must address when deploying AI-driven systems.
We also discuss the growing importance of internationally recognised standards and frameworks, including ISO/IEC 42001 and the NIST AI Risk Management Framework, which provide organisations with practical tools for managing AI-related risks and building trustworthy systems.
A central theme of our contribution is the importance of data security, auditability, traceability and meaningful human oversight. As AI agents become increasingly capable of taking actions autonomously and interacting with multiple digital environments, organisations need robust governance mechanisms to ensure transparency, control and accountability.
In our view, the future of Agentic AI depends not only on technological innovation but also on the ability to balance innovation with responsibility. Sustainable adoption requires practical governance frameworks that enable organisations to realise the benefits of AI while maintaining trust, compliance and effective risk management.
We are delighted to contribute to this important conversation and look forward to supporting organisations as they navigate the evolving legal and regulatory landscape surrounding AI technologies.
KG Legal Kiełtyka Gładkowski
Technology, AI & Digital Regulation Practice Group
See the full text of the contribution here:
Artificial intelligence is entering a new phase of development. While recent years have been dominated by generative AI systems capable of producing text, images, and code, the next wave of innovation is increasingly focused on agentic AI – systems that can plan, reason, take actions, and interact with digital tools to achieve defined objectives with varying degrees of autonomy. Rather than merely responding to prompts, AI agents can execute multi-step tasks, coordinate workflows, and support decision-making processes across organisations.
For the United Kingdom, agentic AI represents a significant opportunity to improve productivity, strengthen public services, and enhance competitiveness across strategically important sectors. However, the successful deployment of these technologies at scale will depend not only on technological progress but also on the development of appropriate governance frameworks, organisational capabilities, and regulatory safeguards.
One of the most promising areas for adoption is the public sector. Government departments, local authorities, and public agencies manage large volumes of administrative processes that are often repetitive, time-consuming, and highly procedural. Agentic AI systems could support public servants by processing applications, managing case files, drafting correspondence, coordinating information across departments, and responding to routine citizen enquiries. In healthcare, AI agents could assist with patient triage, clinical documentation, appointment scheduling, and care coordination, helping to reduce administrative burdens and allowing healthcare professionals to focus on activities that require human expertise and judgement. At a time when public services face increasing demand and resource constraints, such efficiencies could have a meaningful impact on service delivery.
The financial and professional services sector, one of the UK’s most important economic strengths, also presents substantial opportunities. Banks, insurers, law firms, accounting practices, and consulting businesses rely heavily on information-intensive workflows that are often governed by detailed regulatory requirements. Agentic AI could automate compliance monitoring, support anti-money laundering investigations, review contracts, process insurance claims, conduct due diligence exercises, and assist with regulatory reporting. By reducing the time spent on routine analysis and documentation, organisations could improve operational efficiency while enabling skilled professionals to focus on higher-value strategic work.
Significant potential also exists in life sciences and healthcare innovation. Drug discovery, clinical research, pharmacovigilance, and regulatory compliance involve complex processes requiring the analysis and management of vast amounts of information. AI agents could help researchers identify relevant scientific literature, support clinical trial management, monitor safety data, and streamline documentation requirements. Given the UK’s strong research institutions and established life sciences ecosystem, agentic AI could contribute to both improved healthcare outcomes and economic growth.
Beyond knowledge-intensive industries, agentic systems could support manufacturing, infrastructure, transport, and energy. Applications may include predictive maintenance, supply chain optimisation, resource allocation, operational planning, and infrastructure monitoring. In the energy sector, AI agents could assist in balancing increasingly complex electricity networks, improving efficiency and supporting the integration of renewable energy sources. As the UK continues to modernise critical infrastructure and pursue net-zero objectives, intelligent automation may become an increasingly valuable tool.
While the opportunities are substantial, the widespread adoption of agentic AI will depend on overcoming a range of technical and organisational challenges. Autonomous systems must be reliable, secure, and capable of operating within clearly defined boundaries. Organisations will need robust mechanisms for evaluating agent performance, monitoring behaviour, identifying failures, and ensuring that human oversight remains available when necessary. The quality, accessibility, and interoperability of data will also be critical, as AI agents are only as effective as the information and systems with which they interact.
However, technology alone will not determine success. Many organisations continue to view AI as a standalone innovation initiative rather than a catalyst for broader transformation. Effective adoption will require the redesign of workflows, investment in workforce skills, and the establishment of clear governance structures. Employees must understand how AI systems operate, where their limitations lie, and when human intervention is required. Equally important is the allocation of responsibility for decisions made or influenced by AI systems. As autonomy increases, organisations must ensure that accountability remains clearly defined.
These governance considerations are becoming increasingly important as agentic AI systems move from experimentation to operational deployment. Although the UK has generally adopted a flexible and innovation-oriented approach to AI regulation, organisations deploying AI agents are already subject to a range of existing legal and regulatory obligations.
Unlike the European Union, which has introduced a dedicated regulatory framework through the EU AI Act, the United Kingdom has largely favoured a principles-based approach that relies on existing regulators and legal frameworks. This means that organisations deploying AI agents must consider how established laws apply to new technological capabilities rather than expecting a single comprehensive AI statute to provide all the answers.
Data protection law is particularly relevant where agentic systems process personal information. Under the UK GDPR and the Data Protection Act 2018, organisations must ensure lawful processing, transparency, accountability, and appropriate safeguards for automated decision-making. As AI agents increasingly influence decisions affecting individuals, issues such as explainability, fairness, and meaningful human oversight become more significant. Depending on the sector and use case, organisations may also need to consider obligations arising under consumer protection law, financial services regulation, employment law, equality legislation, cyber security requirements, and professional conduct rules.
Alongside formal regulation, an increasingly influential body of soft law is shaping expectations around responsible AI deployment. Guidance issued by the Information Commissioner’s Office (ICO), the Alan Turing Institute, the Centre for Data Ethics and Innovation (CDEI), and government bodies has helped establish practical principles relating to transparency, fairness, accountability, and human-centred design. While these instruments do not carry the same legal force as legislation, they are increasingly used as benchmarks by regulators, procurement authorities, and stakeholders when assessing whether organisations have deployed AI responsibly.
International standards are also beginning to play an important role. Frameworks such as ISO/IEC 42001, the first international management system standard specifically designed for AI governance, provide organisations with structured approaches to managing AI-related risks and responsibilities. Similarly, the NIST AI Risk Management Framework has emerged as an influential reference point for identifying, assessing, and mitigating risks throughout the AI lifecycle. Together, these frameworks are contributing to the development of a common governance language that may facilitate trust, interoperability, and regulatory compliance across jurisdictions.
For agentic AI specifically, governance challenges are amplified by the ability of systems to take actions, access external tools, and interact with multiple digital environments. Organisations will therefore need mechanisms that support auditability, traceability, incident management, and human escalation. Comprehensive logging, approval workflows, access controls, and continuous monitoring are likely to become essential features of responsible deployment. In practice, successful adoption may depend as much on governance design as on technical capability.
Ultimately, the UK’s opportunity lies not simply in adopting more AI, but in deploying increasingly capable systems in ways that generate measurable economic and societal value. The greatest benefits are likely to emerge where agentic AI is embedded within complex, high-volume workflows across both public and private sectors. Yet sustainable adoption will require more than innovation alone. It will depend on a careful balance between technological ambition, organisational readiness, and robust governance. Those organisations that invest early in accountability, risk management, and trust-building measures are likely to be best positioned to capture the benefits of agentic AI while navigating an increasingly complex regulatory and ethical landscape.
Prepared by KG LEGAL KIELTYKA GLADKOWSKI, iSTART1