FIX
Recover value from AI investments that have stalled.
For organizations with licenses, pilots or partial implementations that are underused, unmeasured or politically exposed.
WHAT'S THE AI PROBLEM?
By The Numbers: AI Failure
01 · Pilot outcomes
95%
of generative AI pilots deliver no P&L impact.
MIT. Spend converts into activity and demos rather than measurable earnings.
02 · Project failure rate
80%+
of AI projects fail — twice the rate of standard IT.
RAND Corporation. The gap is execution and decision discipline, not model capability.
03 · Data readiness
85%
of AI models fail on poor or missing data.
Gartner. The binding constraint sits upstream of the model, in access, quality and coverage.
04 · Wasted spend
26%
of AI spend produces no measurable return.
At $1M per month — the reality for one in five organizations — that is $260,000 lost every month.
05 · Strategy vacuum
15%
of employees see a clear AI strategy.
Gallup. Adoption stalls where direction, ownership and priorities are never communicated.
06 · Talent gap
55%
of leaders doubt they can staff AI roles.
Microsoft and LinkedIn. Up to 70% of employees need upskilling, yet 74% of organizations expect to run AI agents by 2027.
THESE ARE NOT TECHNOLOGY FAILURES. They are failures of decision, evidence, data readiness, ownership and adoption — each one diagnosable before the next dollar is committed.
Why leaders call us now.
03 · Stalled pilot
“The demo worked; the operating workflow did not.”
Quality, integration, ownership, adoption, or economics remain unresolved.
02 · Budget or renewal
“We are paying for AI, but cannot show the value.”
A license, vendor, or budget decision is approaching.
04 · Fragmented portfolio
“Every function is buying and building separately.”
Tools, use cases, data practices, and controls are duplicative or inconsistent.
05 · Uncontrolled use
“Employees are already using AI outside approved controls.”
Leadership lacks an inventory, ownership model, or proportionate guardrails.
01 · Board pressure
“The board wants a defensible AI answer.”
Leadership needs a fact-based strategy, investment logic, and accountable next step.
06 · Scaling problem
“One team has a win; we cannot repeat it.”
A promising use case exists, but the organization cannot govern or scale it.
AIRA Audit
The AIRA Process
From AI questions to an actionable plan in four weeks.
WEEK 1
Align
Frame the Business Decision
We establish what matters before evaluating technology.
- Define the business problems and opportunities
- Establish scope, objectives and success measures
- Identify decision-makers and accountable owners
- Inventory existing AI initiatives, tools and experimentation
- Align on the decisions AIRA needs to inform
Deliverable · AIRA Assessment Charter
WEEK 2
Assess
Understand Your Current State
We examine how the business runs and what AI requires.
- Review priority workflows and processes
- Assess relevant data, systems and technology
- Evaluate existing AI tools, pilots and usage
- Identify organizational, data and capability gaps
- Develop an evidence-based map of potential AI opportunities
Deliverable · Readiness & Opportunity Map
WEEK 3
Evaluate
Determine What Is Worth Pursuing
Initiatives are weighed on value, feasibility, readiness and risk.
- Evaluate expected economics and business impact
- Assess data and technical feasibility
- Identify implementation, governance and operational risks
- Classify each initiative: Proceed, Prepare, Repair, Stop
Deliverable · AI Opportunity Portfolio
WEEK 4
Mobilize
Turn the Findings Into Action
We convert the assessment into a prioritized, executable plan.
- Finalize leadership recommendations
- Prioritize initiatives based on value, feasibility and readiness
- Define ownership, controls and success metrics
- Identify immediate capability and data requirements
- Establish near-, medium- and longer-term priorities
- Build a practical 30/60/90-day action plan
Deliverable · Executive AI Roadmap
What you receive.
Illustrative
Executive decision page
The one-page answer leadership can use.
Illustrative
AI portfolio table
What to fund, repair, scale, hold or stop.
Illustrative
Use-case decision card
The evidence and assumptions behind each recommendation.
Illustrative
Evidence-test summary
A technical verdict tied to pre-agreed thresholds.
Illustrative
Risk & remediation register
The conditions required before launch or scale.
Illustrative
90-day roadmap
Named owners, milestones, dependencies and decision gates.