Legal Tech Trends in 2026: Insights for Business and IT Leaders – iManage

Looking ahead to 2026, business and IT leaders in legal face a rapidly evolving technology landscape shaped by AI advancements, security challenges, and shifting governance priorities. Industry experts from iManage share their insights on the key trends set to redefine organisational strategies and operations in the coming year.

Jan Van Hoecke, VP AI Services, iManage:

AI hallucination goes from “crisis” to management

In 2026, the AI hallucination crisis will reach a critical juncture as firms realise they must learn to coexist with the current fundamentally imperfect technology – until a new technology comes into play that can effectively address the issue. The focus will shift from AI hallucination ‘crisis’ to ‘management’.

As the legal industry deliberates who carries the liability for AI’s mistakes and inaccuracies – the tool makers or the users – firms will stop waiting for vendors to solve the problem and take matters into their own hands. They will adopt a variety of pragmatic risk mitigation strategies – from double and triple-checking work, and enforcing human oversight for high-stakes decisions, to taking hallucination insurance policies. Users will start driving the hallucination conversation – both by building systematic defenses into how they use AI and by forcing vendors to accept shared responsibility through better documentation and clearer model limitations.

Middleware AI apps squeeze

Given the essential link between data and AI, middleware companies that specialise in building custom applications layered on top of data platforms will begin to get pushed to the margins, forced to compete on niche features – while the core value of data and insight is captured by the platform owners. The true leaders will be those organisations that both own and manage their data, while also offering an AI-powered interface that enables users to interact with their data securely and efficiently, fully leveraging the capabilities of modern AI technology.

Agentic AI reality check  

2026 is the year when agentic AI will get a reality check, as the gap between marketing promises made in 2025 and their actual competencies will become starkly visible. As adopters in the legal industry share the mixed successes of agentic AI, the market will begin to differentiate between true autonomous agents and the clever workflow wrappers.

Currently, many products promoted as AI agents are, in reality, rigidly programmed systems that simply follow predefined paths. They cannot independently plan or adapt in real-time to accomplish tasks. The current evolution of AI agents closely resembles the development of autonomous vehicles: early self-driving cars could only maintain lane position by relying strictly on preset instructions, and likewise, today’s AI agents are limited to executing narrowly defined tasks within established workflows. True autonomy, where AI agents can dynamically perform and solve complex problems better than humans and without human intervention, remains, for now, an aspirational goal.

Paul Walker, Corporate Legal Lead, iManage:

Prepare for increased workloads, thanks to best friend ChatGPT

The landscape of formal complaints is rapidly transforming. Typically, grievances arrived as brief emails and were reviewed by the relevant department, following established procedures. Today, AI tools like ChatGPT are enabling individuals to craft sophisticated legal documents as complaints. Now routine complaints arrive as comprehensive, multi-page reports – often complete with articulate legal arguments that standard departmental teams or internal staff cannot effectively handle. These complaints require specialised expertise to review and resolve.

This phenomenon will dramatically accelerate in 2026, creating significant challenges across organisational departments. Corporate legal teams will face mounting workloads as the complexity of grievances increases. Standard operational and legal procedures require a complete overhaul, as both internal and external stakeholders have access to professional-level document-generating capabilities – potentially increasing organisational risk and legal exposure.

Governing AI output will become a priority

Up until now, organisations have focused on capturing and documenting information and communication on tasks and activities – from email correspondence, Microsoft Teams chats, Slack conversations – within digital/matter files.

In 2026, as AI agents develop, capturing and maintaining the communications of this new “labour” force – as part of the existing digital/matter files and document histories – will become a business imperative. As AI agents assume greater decision-making authority, organisations will need robust frameworks to track, oversee, and ensure accountability for the actions and outputs of AI in their business.

Sam Grange, AI Engineering Lead, iManage:

“What am I paying for?”

As legal tech buyers increasingly demand proof of AI capabilities, vendors without an evaluation hub will find themselves exposed. Buyers will insist on knowing “what are we paying for?”

The AI conversation has moved from “we need AI agents to increase productivity” to “what exact capabilities are we getting from AI?” There is growing recognition that without an evaluation hub that sets standards, actively governs data, provides starting points for AI adoption, and so forth, organisations may simply be buying glorified AI wrappers at premium prices and with no guarantee that the technology will deliver tangible, reliable value to the business.

Open innovation-led AI systems are the future

2026 will see the legal technology landscape pivot decisively toward open innovation ecosystems over closed integration approached to AI. As organizations demand flexibility to integrate AI tools on their terms rather than vendors’ terms, open innovation frameworks will dominate.

While proprietary, closed AI partnerships have served their purpose by maintaining tight control – and with good reason too – the industry will embrace open innovation-led AI systems where LLM providers enable secure, governed interoperability without gatekeeping.

This shift mirrors a broader market evolution. Apple, historically notorious for closed standards and developer control, is abandoning its walled-garden approach in favor of open integration, with the arrival of Model Context Protocol (MCP), a standard for connecting AI with external tools and data.

The future belongs to platforms that empower users to build their own secure integrations, not those dictating partnerships from above.

Manuel Sanchez, Subject Matter Expert, Security and Compliance, iManage:

The role of AI in data governance: from manual chaos to automated control

In 2026, AI-powered document classification and governance systems will transition from emerging technology to essential infrastructure for organisations managing high-volume information flows. AI will be able to automatically classify all manner of documents into the right document types, and apply appropriate metadata and retention policies, without human intervention.

This shift will help automate data governance to a large extent. Manually classifying exponentially growing data volumes has become nearly impossible. Trusted AI-based systems will instead monitor central repositories in real-time, identifying document types, detecting personally identifiable information, and automatically applying retention policies based on document content. This will dramatically reduce classification errors, make search and document retrieval instantaneous, and automate compliance. Organisations will be able to see significant improvements across the board.

Cloud chaos and the governance crisis

In 2026, companies will experience a deepening governance crisis caused by the exponential growth of unstructured data combined with unclear cloud accountability, resulting in serious compliance risks. Organisations will be compelled to adopt new approaches and governance architectures or face severe consequences.

The governance and compliance risk challenges are compounding simultaneously. Unstructured data – i.e., the emails, documents, and information lacking clear categorisation – continues to grow rapidly, creating governance blind spots that traditional controls cannot address. Meanwhile, the proliferation of cloud applications adopted by teams and departments, provided by multiple vendors across a mix of hosting services, such as Azure and AWS, is making the shared responsibility model increasingly muddy. Organisations struggle to map accountability boundaries between themselves, application providers, and cloud hosts. This ‘grey’ zone is creating vulnerabilities that the bad actors are increasingly exploiting.  While vendors and implementation partners attempt to clarify these boundaries upfront, the sheer volume of cloud applications is making consistent, wholesale governance at the enterprise level nearly impossible with the current approaches.

Joe Logan, CIO, iManage:

Data residency and geopolitical complexity will make vendor trust critical

With continuously evolving geopolitical issues and divergent data residency requirements across jurisdictions, organisations will partner with cloud vendors who are capable of managing multi-jurisdictional compliance complexity, making “trust” the primary competitive differentiator for selection.

Global organisations face an impossible task of meeting the highest standards of compliance across every single regulation and jurisdiction, while maintaining operational agility. Trust will be the only currency – based on verifiable proof that the cloud vendor selected genuinely satisfies the complex multi-geography data privacy, security, and residency requirements. Vendors demonstrating robust third-party attestations across a wide variety of evolving frameworks –  from ISO and CSA STAR; FedRAMP, IRAP and Cyber Essentials Plus; EU-US Data Privacy Framework; through to NIST AI Risk Management and EU AI Act – will capture enterprise market share, while those lacking credible compliance infrastructure will face elimination.

AI-as-a-service set for acceleration

AI-as-a-service will expand rapidly in 2026, mirroring the internet boom of the 1990s and the SaaS explosion in the 2000s’ teens. Dominant platforms will emerge in legal, healthcare, pharmaceutical, and research sectors through contextualised, industry-specific offerings.

The AI-as-a-service market currently exists in a nascent, fragmented state where organisations deploy varying approaches – from “small box” solutions for internal use to experimental implementations that today lack governance and formalised structures.  Agentic systems like Microsoft Copilot, embedding sophisticated AI capabilities within familiar workflows, illustrate this trend.

As successful implementations grow organically, winning platforms will emerge through their ability to package and integrate superior workflows into contextualised services for industry-specific sectors while also addressing evolving sector-specific regulatory and operational requirements.