A Deloitte Canada Insurance Point of View 2026
The Insurance Company of 2035
By 2035, most insurers will be using AI across the enterprise. The difference between leaders and the rest will be how deeply it has changed the way the business actually runs - how decisions are made, risk is assessed and customers are served.
About this point of view
Architecture decisions are easier to make when the destination is clear. This paper, the second in the Compounding Intelligence series, looks at the insurance enterprise we see taking shape: one where AI is embedded in day-to-day operations, and where human roles shift toward the decisions, relationships and accountability that still require judgment.
Each paper in the series stands alone. This one is about where the industry is heading and what it means for how work gets done. How to build toward that future, and who should own the intelligence it generates, are questions taken up in the papers that follow.
01 · The 2035 vision
A view of where the industry is heading
By 2035, AI itself will not differentiate insurers. Most will have deployed it broadly. The difference will be whether those capabilities have changed how the business works, rather than simply adding another layer of technology.
That difference will show up across claims, underwriting, distribution and customer engagement. The leaders will have connected the data, workflows and decisioning underneath those functions so the capabilities reinforce one another rather than operate independently.
In this future, a claims event is triaged the moment it arrives. Coverage is validated in real time, the policyholder is kept informed throughout, and the case reaches a human only when human judgment is genuinely required. The adjuster's caseload is smaller, but every remaining case is more complex: contested claims, emotionally sensitive situations, and the decisions where experience and judgment make a material difference to the outcome.
Underwriting becomes more continuous as well. Risk models update as experience, loss patterns and insured behaviour change, giving underwriters a more current view of risk. The real shift is not the sophistication of any one model; it is the way data, decisions and workflows are connected. The String of Pearls explores how to sequence that change, while Owned Intelligence addresses who controls the intelligence it creates.
AI will no longer be seen as a discrete capability. It will be embedded in an insurance organization's DNA, scaled horizontally across functions, workflows, and roles. Success will depend on how well insurers connect their data, technology, and people to deliver impact at scale.
02 · How work changes
Four roles, redesigned around judgment
As AI scales, the most consistent change we see is not simply that work disappears. Routine, transactional activity moves toward automation, while human effort shifts toward judgment, accountability and interaction. The harder part is often redesigning the work itself: deciding what agents should do, where people need to stay in the loop, and how the two work together day to day.
Underwriter→Risk Strategist
When agents handle data gathering, guideline application, and initial scoring, underwriters stop spending their days on straightforward placements. What reaches them instead is complex, non-standard, or genuinely uncertain. Routine volume falls, but the judgment required on every remaining case rises substantially, making it a more demanding role by any measure.
Adjuster→Complex Case Specialist
The 2024 catastrophe season produced approximately 250,000 claims in five weeks (Insurance Bureau of Canada, 2025). Carriers managed it through surge staffing and third-party support, but at a significant cost and with variable consistency. The ones that managed it well had built systems that could triage, validate, and route at volume, freeing adjusters for the contested claims, sensitive situations, and cases where empathy and experience genuinely matter. Those cases reach a human. The volume work does not.
Actuary→Intelligence Architect
The actuary's role also changes as insight becomes more continuous. Less time is spent producing periodic analyses; more is spent interpreting signals, challenging model outputs, refining assumptions and shaping pricing and product decisions. Governance, validation, bias assessment and regulatory compliance remain core to the role. What changes is the frequency of the judgment and its visibility across the organization, including how uncertainty is explained to management, regulators and boards.
Advisor→Relationship Architect
As agents handle product research, suitability screening, and routine service interactions, advisors have more capacity for the client conversations that are genuinely relationship-defining: complex financial planning, life transitions, and the moments where human presence and continuity matter most. The advisor's comparative advantage deepens as agents absorb the transactional work.
The pace will vary, but these role shifts are already starting. The important question is whether insurers design the human and agentic workforce together or allow it to evolve one use case at a time. The AI Orchestrator, the fifth paper in this series, looks at what that requires in practice.
03 · Closing
Questions worth asking now
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Q1 |
Are the human and agentic workforce being designed together, or is workforce evolution expected to follow the technology deployment? |
Q2 |
Which of your core roles, redesigned around what humans do best and what agents do best, would most change the economics and quality of the function? |
Q3 |
If these shifts arrive on their current trajectory, will they have happened in your organization by design or by accident? |
The Compounding Intelligence series
Five standalone points of view on scaling agentic AI in insurance. Each paper is written to be read on its own; together they form a single argument.
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1 |
Why record AI investment is not compounding, and why the window for foundational choices is narrower than it looks. |
2 |
This paper The Insurance Company of 2035 The destination: how an agentic enterprise runs, and how four core insurance roles change. |
3 |
The strategic case for controlling what your AI learns, across six dimensions, and the tiered architecture that makes it practical. |
4 |
Reimagining the value chain from business outcomes, and sequencing capabilities so each inherits the intelligence of the last. |
5 |
What enterprise orchestration requires in practice, and six questions that surface the decisions worth making now. |
Melissa Carruthers
