Cathy Goodman global chief knowledge office and AI lead at Kennedys explains why Artificial Intelligence will create new risks and new opportunities for 2026.

The legal and professional services sectors are undergoing major transformation driven by AI, with the focus shifting beyond technology adoption to mandatory literacy, organisational structuring, and the emergence of entirely new risk classes.

AI literacy and reskilling

A key prediction is that AI literacy will become mandatory across all organisations,  mirroring established requirements for training in areas like data protection, anti-money laundering, and modern slavery. “Providers” and “deployers” of AI  are already (since 2 February 2025) required to provide AI literacy training to their staff under the EU AI Act.

The necessity for and importance of providing and ensuring foundational AI literacy within all organisations feeds into a broader and more urgent prioritisation by businesses to upskill or reskill for all roles, not just digital-first positions. Organisations are in a crucial transition period where they must make a conscious decision to upskill their workforce at all levels. Failure to support the development of technology expertise risks a widening knowledge gap, as generative AI (GenAI) and automation erode traditional entry-level tasks. There are many opportunities to leverage AI and emerging technologies to nurture legal and professional learning. In some cases it will require reimagining how we collect, transfer and share knowledge to successfully develop talent. The impact of the need for AI literacy will fundamentally shift recruitment strategies and business operating models across the industry as technology expertise is expected for roles that did not historically require technology expertise or need it. It also reinforces the importance of the “human in the loop” role: adequate guardrails for ensuring safe and proper AI use doesn’t just mean checking outputs, it means understanding at least the basic underlying mechanics of AI tools.

Deployment and automation of AI

The use of advanced AI will progress rapidly from using multiple point solution tools to leveraging embedded, autonomous workflows. The prediction is that agentic AI will become the norm for business operations and in our personal lives, autonomously making decisions and taking actions. AI agents will become embedded across core functions in both the legal sector and the insurance industry, including claims, underwriting, and legal workflows. Provided AI literacy support is in place, workforces will naturally upskill as they are facilitated by AI to work more quickly and more accurately with larger datasets, on complex processes.

Global regulatory environment

The global regulatory landscape will become more defined, affecting directly the deployment and use of AI. This will involve:

• Global AI Regulation: The EU AI Act and the UK AI Bill will set a high bar, while US deployment will be shaped by frameworks and guidelines issued by bodies like the American Bar Association (ABA), all of which will directly influence how AI is used in legal work, underwriting, and claims processing.
• Model governance standards: We will see an increase in supervisory bodies such as the SRA for law firms and financial services regulators issuing more explicit model governance standards for AI systems. This will extend to an expansion of operational resilience mandates, such as DORA and PRA rules, to explicitly cover AI systems and the associated third-party dependencies.
• Collaboration between global government and supervisory bodies is necessary for a cohesive and appropriate approach to AI regulation.

AI as an insurance risk

A critical challenge for the insurance industry will be how to underwrite the risks of AI itself. As AI systems make errors, new, unpredictable risks will emerge. This difficulty is compounded by a lack of prior claims history and, at present, limited understanding of the full scope of potential failures, leading some insurers to limit underwriting cyber risk which often encompasses AI-related exposures. A concerted effort will be required to develop a framework for properly underwriting AI as a distinct insurance risk.

AI as an insurance enabler

We expect to see the introduction of more GenAI “copilots” to support claims, underwriting and legal review processes. This will amplify the existing urgency to get data in good order so that businesses can leverage AI to identify trends and patterns for risk analysis and accurate insights. Law firms and insurance businesses alike will invest heavily in data hygiene, tech tool interoperability and API-based architecture.

New legal and ESG challenges

The increased use of AI will create new challenges for legal certainty and sustainability:

• Fraud and AI-generated evidence:  AI-generated evidence, and claims that create disputes over their authenticity and liability, will continue to rise . This will necessitate the development of new guidance and training to alert legal and other professionals to digitally altered or inauthentic submissions, and the wider use of technologies to pre-empt and prevent such submissions.
• Contractual certainty: Contracts governing the use of AI must incorporate clear provisions on explainability, transparency, auditability, ethical, and safe use. Organisations will be forced to gain greater visibility into the AI practices of their providers’ supply chains, and suppliers will need to provide greater transparency into their AI tools than they have done to date.
• Sustainability: The environmental impact of AI, specifically its significant water and energy consumption for training models large infrastructure needs will face intense scrutiny. The demand for GenAI and consequent increased demands on electricity could counter net-zero targets. This issue will become integrated into existing frameworks like sustainability reporting regimes (CSRD, the EU AI Act and related regulations).