51%
run both coding agents and business agents, yet only 16% report well-defined processes for AI use.
New Research · 2026
The Hidden Disconnects in Enterprise AI
Tactics for aligning coding agents, business agents and the APIs they depend on
89% of organisations say teams across the enterprise are already using coding agents, but most run them on foundations that were never designed for autonomous systems. Based on 114 practitioner surveys, 16 enterprise interviews and 183 sources, this report reveals the 6 structural disconnects that stall enterprise AI before it pays off, and how to fix them.
By the Numbers
What our research found across 114 practitioners
and 16 enterprise leaders
23%
have a scoring model for prioritising AI use cases against business goals.
44%
are unsure how often AI access to their own systems is monitored.
28%
measure the impact of AI in terms of productivity or business value.
What you'll find inside
Two agent strategies. One hidden problem.
Enterprises are investing in coding agents and business agents but treating them as two separate problems, with two separate foundations, two separate governance approaches, and duplicated risk.
This report shows what that divide is costing you, and gives both your platform engineering team and your AI innovation team a platform response to each of the six disconnects.
Why coding agents and business agents are being adopted along separate paths (51% run both, but only 16% report well-defined processes for AI use), and what it costs every time those stacks have to share data, credentials, or governance.
Why going AI-first without being API-first means your agents inherit every broken workflow, undocumented endpoint, and inconsistent error message that was already a problem before AI arrived, when only 30% have assessed their APIs for AI readiness.
Why most enterprise AI governance is symbolic: organisations have written policies, access controls, and approval lists in place but 44% still don't know how often their agents are accessing their own systems.
The architecture shared by enterprises with genuine production confidence: a single platform layer underneath both coding and business agents. Organisations already in production are 7x more likely to have formally assessed API readiness than those still piloting.
A platform response to each of the six disconnects, plus a seven-point maturity checklist written for both the platform engineering leader and the AI innovation leader, so both teams can use the same research to align strategy and demonstrate ROI.
The findings at a glance
The Six Disconnects
Coding agents outside the platform model
Rigidity over flexibility
AI-first without API-first
Projects without purpose
Symbolic security
Limited sandbox leverage
Written for the people making the calls
This report is most useful if you are:
a CTO, VP Engineering, or Head of Platform
who evaluates AI agent infrastructure.
an AI or ML Lead
who is responsible for production deployments at scale.
a Senior Executive
who is being asked to sign off on AI investment without a clear view of whether coding and business agents are working together or duplicating effort.
a Technical Leader
who knows the shortcuts being taken to hit AI deadlines and needs the data to make the case for doing it properly.
About the research
Independent research.
Real data.
This report is based on a survey of 114 AI and API practitioners, in-depth interviews with 16 enterprise leaders responsible for AI implementation, and a review of 183 reports, articles and papers.
Research was conducted between March and May 2026. Respondents span 27 countries across 5 continents, weighted toward technology and banking or finance, and toward senior architecture and platform roles. Findings should be read as directional practitioner insight rather than a statistically representative enterprise benchmark.
Written by Erik Wilde, Sean Blanchfield and Mark Boyd. Interviews were held in confidence, and where findings from specific organisations are cited, identities have been protected unless explicit permission was given.
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