Top trends in enterprise architecture 2026

Capgemini publishes top-trends pieces for banking, insurance and financial services each year. BCG runs the AI Radar. PwC publishes its UK economic predictions. McKinsey runs its State of AI series. Nobody publishes a working architect's top-trends piece for the enterprise architecture practice itself.

This is the first annual version of one. It is written from the practitioner side and is calibrated against what I see in my own work and in conversations with peers in the function.

Trend 1: the EA function carries more direct

delivery weight

In 2024, the EA function was largely a reviewing function: standards, frameworks, governance reviews, target-state architecture. By the end of 2026, the firms taking AI seriously have moved the function into direct delivery on platform components (agent platform, identity platform, data platform).

The shift is real and not yet reflected in most EA function staffing. The function that delivered well in 2024 is under-resourced for the 2026 demand.

Trend 2: TOGAF and the equivalent frameworks need

adaptation, not replacement

TOGAF and the other established EA frameworks were designed for an environment with slower change, more deterministic workloads and clearer ownership boundaries. The agentic era stretches all three. The frameworks still work but they need adaptation: faster iteration of the architecture position, explicit treatment of stochastic workloads, clearer rules for agent-driven integration.

The firms claiming TOGAF is dead are overstating the case. The firms that ignore the adaptation question are under-stating it.

Trend 3: the commercial EA tool market is

restructuring

I wrote about this in the EA tool market has 18 months and the intervening twelve months have, if anything, accelerated the shift. The major commercial EA tools are absorbed into broader platforms or are losing relevance to AI-augmented internal alternatives. The EA function has to make a deliberate choice rather than inherit one.

Trend 4: architecture decision records become a

living practice again

ADRs were a 2010s discipline that decayed in many firms. The agentic era has reinvigorated the practice for a specific reason: AI agents can read ADRs and use them to inform code generation, refactoring recommendations, and integration design. ADRs that were a documentation chore are becoming an operational artefact.

See The evolving role of architecture decision records in the age of generative AI.

Trend 5: fitness functions become measurable

Architectural fitness functions have been a concept since the early 2010s but were rarely measured in practice. The observability investment around agent platforms has, as a side effect, made many of the fitness function metrics genuinely measurable. The EA function can now operate against measured fitness functions rather than asserted ones. See Architectural fitness functions: a practical framework.

Trend 6: enterprise architecture and the regulatory

function move closer together

The convergence is structural. The regulatory function has more direct dependency on architectural choices (AI use cases, data residency, agent governance, model inventory). The architecture function has more direct exposure to regulatory enforcement (SS1/23, EU AI Act, operational resilience). The two functions have to work as one team, not as two adjacent functions.

Firms that have not made this organisational shift will do so in 2026 or 2027.

Trend 7: MCP and equivalent standards become the

operating norm

Twelve months ago, MCP was a curiosity. Twelve months from now, it will be assumed. The firms that have not adopted it will be the exception, and the cost of being the exception will be measurable. See MCP is the most important enterprise standard nobody is implementing for the context.

Trend 8: the platform-team-vs-product-team boundary

gets redrawn

The DevOps consolidation of the late 2010s blurred the boundary between platform teams and product teams. The agentic era has prompted a clearer redraw: platform teams own the foundational components (model serving, agent platform, observability, identity); product teams own the use cases that consume them. The architecture function has to be explicit about which is which.

Trend 9: the architecture function develops a

buy-side discipline

The vendor selection decisions in 2026 are larger and more consequential than in any previous EA cycle. Foundation model vendors, agent platform vendors, SaaS vendors with embedded AI. The architecture function has to develop a buy-side discipline that operates at the level the decisions require, with proper criteria, proper diligence and proper negotiation support. Most firms have not invested in this capability.

Trend 10: the architect-as-builder model gains

traction

A small but growing number of architecture leaders are shipping code, not just specifications. The Meridian and CANVAS systems I built at Sonnedix sit in this category. The pattern is not appropriate for every firm or every architect, but where it works it delivers materially faster than the specification-driven model. See the Meridian case study and the CANVAS case study.

Where this leaves the function

The EA function in 2026 is materially different from the function in 2022. More delivery weight, more regulatory exposure, more direct ownership of platform components, more accountability for vendor decisions.

The firms whose EA functions adapt to this carry the agentic transition well. The firms whose EA functions remain in the reviewing posture will struggle.

This piece will be revisited annually. The 2027 version will mark which of these trends accelerated, which plateaued, and which were overstated.