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AI Looking into 2026: What law firm leaders should be paying attention to

Akber Datoo reflects on AI trends as 2026 approaches. He explains that AI capability continues to advance and has become structural, used daily by staff and trusted for complex analytic tasks. The next shift is toward agentic AI that runs workflows and raises questions about accountability and governance. He argues that guardrails are now a leadership obligation and that firms must embed policies, training and alignment to use AI safely and defensibly.

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Akber Datoo

LinkedIn

·4 Jan 2026
inLinkedIn
Text-led LinkedIn post

Executive Summary

Akber Datoo reflects on AI trends as 2026 approaches. He explains that AI capability continues to advance and has become structural, used daily by staff and trusted for complex analytic tasks. The next shift is toward agentic AI that runs workflows and raises questions about accountability and governance. He argues that guardrails are now a leadership obligation and that firms must embed policies, training and alignment to use AI safely and defensibly.

Key Takeaways

01

Akber Datoo reflects on AI trends as 2026 approaches.

02

He explains that AI capability continues to advance and has become structural, used daily by staff and trusted for complex analytic tasks.

03

The next shift is toward agentic AI that runs workflows and raises questions about accountability and governance.

Key Quote

AI is no longer experimental – it’s structural. We’ve crossed the threshold from pilots to embedded capability

Excerpt

AI Looking into 2026: What Law Firm Leaders Should Be Paying Attention To. As we turn into 2026, one thing is clear: AI has not hit a wall.

Despite the noise around bubbles, regulation or ‘AI fatigue’, the reality inside law firms tells a different story. AI capability continues to advance rapidly and confidence at leadership level is materially higher than it was at the start of 2025.

Three shifts matter most: AI is no longer experimental – it’s structural; the next phase is agentic AI that runs workflows and requires accountability; and guardrails are no longer optional as AI governance becomes a leadership obligation.

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