Tech Legal Outlook 2026

The technology investment landscape in 2026 continues to evolve, shaped by a mix of shifting trade dynamics, targeted pro-growth reforms and regulatory fragmentation. These developments present both opportunities and challenges for dealmakers, who are responding with increasingly agile and creative approaches to structuring cross-border transactions. Interest remains strong in high-growth areas such as AI, digital infrastructure, SaaS, and fintech, supported by substantial dry powder across private equity and venture capital.

With a growing body of digital regulation, investors are placing greater emphasis on compliance, governance, data stewardship, and operational resilience, in investment decisions and exit planning. Heightened scrutiny around antitrust and national security – particularly in cross-border contexts – is influencing deal timelines and execution strategies. 

IPO activity is recovering in select regions and segments, notably AI and cybersecurity, while SPACs are re-emerging as flexible alternatives. Legal foresight and regulatory fluency remain central to navigating complexity and unlocking long-term value. 

Read more: Tech M&A and Investment: Legal and regulatory complexity shaping investment flows and driving innovative deal structuring

In 2026, tech M&A is being increasingly shaped by geopolitics, with greater national security, economic resilience, and tech sovereignty considerations being factored into merger control reviews. Brussels has signalled a modernised approach, encouraging innovation, resilience and ‘European champions’, with the potential introduction of an innovation shield/safe harbour for pro-competitive scale ups. Meanwhile, the UK’s growth-focused stance has seen the CMA shift from ‘policing’’ of cross-border deals to more targeted interventions where other regulators are actively reviewing.

In the US, while continuing to closely review transactions, the current administration has been more flexible in adopting remedies to resolve concerns. Non-competition issues such as ESG policy, labor and national security are also increasingly influencing reviews. China is sharpening below threshold call-ins, focussing on strategically sensitive sectors (in particular, semiconductors) amidst geopolitical volatility.

This sets a broad risk landscape for tech M&A, including smaller, less visible transactions. However, for deals that are reviewed, expect greater multi-agency coordination and more pragmatic conditional clearances.

Read more: Market power meets political muscle: Navigating the tech merger control landscape

Financial infrastructure is rapidly digitalising, a transformation requiring huge amounts of investment. Brookfield is estimating a $4 trillion private equity opportunity across the platforms underpinning the global financial economy. M&A activity is surging with consolidation a key trend and numerous mega deals over $1 billion: all driven by the need for scale, efficiency, and innovation to enhance competitiveness.

Traditional financial market infrastructures – trading venues, clearing, settlement, and payment systems – are replacing legacy frameworks with modern, tech-enabled architectures. In tandem, a new generation of digitally native platforms is emerging, designed for real-time settlement, smart contracts, and tokenised asset trading. While relatively asset-light, these platforms share infrastructure traits such as scalability, resilience, and deep ecosystem integration. This dual technological shift is fuelling investment, spawning ventures, consortia, spin-outs, and divestments.

Governments are also modernising financial systems for consumers, with digital identity, e-signatures, and data-sharing protocols becoming foundational. Fintech infrastructure – like DLT networks for digital assets and API gateways – is attracting investment as regulatory clarity, particularly in the US, is emerging.

Read more: Digital Financial Infrastructure: investing in a new financial architecture

Agentic AI marks the next evolution in AI, moving beyond generative AI’s content creation to autonomous execution of complex tasks. Unlike prompt-driven models, agentic AI acts toward defined objectives with minimal human input, combining reasoning, planning, and adaptability.

Adoption is already underway, with agents embedded in enterprise systems to orchestrate multi-step workflows. Protocols enabling autonomous agent-driven payments are emerging – signalling the convergence of AI and digital assets. 

This shift challenges legal norms around consent, liability, IP and data governance, while raising critical questions around accountability and security concerns. Regulatory frameworks will need to adapt: expect regulators to explore new accountability models, mandatory transparency requirements, and sector-specific guidance, with cross-border compliance remaining complex.

For businesses scaling agentic AI, robust validation, workforce upskilling, informed user consent mechanisms and human-in-the loop safeguards are essential to building trust. Legal teams must adapt contracts, governance, and risk frameworks to ensure responsible deployment and mitigate legal and operational risks.

Read more: Digital commerce redefined – The growing impact of agentic commerce 

Read more: Agentic payments: Reshaping online shopping around the regulatory perimeter

Read more: The rise of the digital employee – Navigating employment law risks in the age of agentic AI

Organisations face escalating data and cyber risks amid geopolitical instability, expanding digital ecosystems, and widespread AI adoption. Generative and agentic AI represent a new threat paradigm, with state-sponsored attacks increasing in speed, scale and sophistication.

The fallout – operational disruption, data compromise, and regulatory scrutiny – can result in multimillion dollar losses. Yet despite increased cyber and AI spending, few companies have implemented robust strategies to counter these threats.

With over 80% of enterprises expected to integrate generative AI by 2026, siloed governance models are no longer sufficient. These risks are deeply interconnected: a data breach can compromise AI models, while poorly governed AI amplifies data and cyber threats through indirect prompt injection attacks.

This convergence demands a fundamental shift in risk management. Data, cyber, and AI risks must be managed holistically together with the protection of proprietary algorithms. Organisations integrating these disciplines into unified governance frameworks will be better positioned to build operational resilience, meet evolving global regulatory obligations, and preserve stakeholder trust.

Read more: Addressing the increased threat landscape with a holistic approach to data, cyber and AI governance

Read more: Protecting proprietary algorithms in 2026: A strategic imperative