Why we created this report
AI has moved from experimentation to expectation. Leaders are being asked to invest, teams are trialling tools, and roadmaps are being written, but measurable outcomes remain inconsistent.
In our work with organisations across sectors, we kept seeing the same pattern: AI ambition was high, but progress was slow, fragmented, or stalled. We wanted to understand why.
So we asked over 100 organisations how they were using AI, and the result is a clear picture of the AI Readiness Gap, and what organisations can do about it. Read it here.
What we wanted to learn
This research set out to answer five practical questions:
- Where are organisations actually investing in AI?
- What outcomes are they achieving, and where are they plateauing?
- What is really blocking progress: skills, tools, budget, or infrastructure?
- How do challenges differ between enterprises, scale-ups, and SMEs?
- What do successful organisations do differently?
What the data revealed
- The Experimentation Trap
- 90% of organisations are using off-the-shelf AI tools, but most remain in low-impact, individual productivity use cases.
- Organisations that embed AI into products and core workflows are far more likely to report high success.
- Infrastructure is the real blocker
- Legacy systems, siloed data, and poor integration are the biggest barriers to AI adoption.
- Efficiency is the goal, not the outcome
- Efficiency and automation are the most common AI objectives, yet they have the lowest success scores.
- Many AI problems aren’t AI problems
- Disconnected systems, weak UX, and manual workflows are often better solved through integration, design and modern architecture.
- AI is exposing digital maturity gaps
- AI is acting as a stress test for data quality, governance, and technical foundations.
Who is this report for
This report is designed for
- CTOs and technical leaders planning AI adoption
- Product leaders embedding AI into digital products
- CIOs and transformation leads modernising legacy systems
- Operations leaders looking to automate complex workflows
- SMEs concerned with security, compliance and risk
If your organisation has AI ambition but limited measurable return, this report will help you understand why.
What you’ll get from this report
Download the full report to access:
- Cross-sector AI investment and success benchmarks
- A breakdown of adoption patterns by organisation size
- The AI Readiness Gap explained in practical terms
- A framework for diagnosing stalled AI initiatives
- A roadmap for moving from experimentation to integration
Plus, immediate access to:
- A practical AI readiness self-assessment checklist
- A simple way to evaluate your current position across data, systems, and integration, and quickly identify where you’re likely to be blocked.
- A free AI Discovery Workshop
- A 30-minute session with our team to help you sense check where AI could deliver real value, identify technical or organisational constraints and prioritise the next steps based on your current setup.
- Please note there is only a limited number available each month.
Why it matters now
Nearly 80% of organisations plan to increase AI investment in 2026. Those that fix their data, systems, and integration capability first will see measurable value. Those that don’t risk remaining in perpetual experimentation. The report should help organisations decide where to focus before scaling spend.
The research
- 100+ organisations surveyed
- Startups, scale-ups, SMEs, and enterprises
- Public sector and private sector representation
- Technical and non-technical respondents
- Quantitative survey data and delivery insight combined
Access the report
Download the report to get the insights, assess your readiness, and take your first step towards meaningful AI adoption.
