For the HR AI transformation leader
You are under pressure to deliver AI wins inside HR in a market moving faster than your function’s readiness to absorb them. The model is rarely the problem. The agent is rarely the problem. No instrument in your stack assesses whether HR is ready for what the vendors are pitching. The Ikona AI Diagnostic does.
Here is how the diagnostic works.
Built by people analytics leaders from Amazon, Google, and Facebook, with ML engineering from Amazon, Expedia, and Merck.
The situation
MIT NANDA reported that 95% of enterprise AI pilots produce zero measurable P&L impact. The reason is not the model — the model is fine. The reason is that the work the AI is supposed to augment has never been captured in a form an AI can use. Vendors pitch AI horizontally; your CHRO asks vertically; the gap between vendor claims and organizational reality is where your credibility lives or dies.
Your peers have their own instruments. People Analytics has surveys and dashboards. HR Technology has system assessments and vendor scorecards. Neither tells you whether a specific AI opportunity can deliver inside the specific governance, data flow, and operating model of your function. That question has never had a purpose-built instrument.
The Ikona AI Diagnostic is that instrument. It runs across the scope of HR, benchmarks against our Ground Truth framework, and produces the AI Opportunity Charter. Not a vendor comparison. Not a capability matrix. A clear-eyed read of which AI opportunities you should take to the CHRO first.
What the Ikona AI Diagnostic assesses
Four parallel threads, each benchmarked against our Ground Truth framework. AI readiness sits at the center; the other three determine whether any of it can deliver. AI deployments fail when the supporting context was never assessed. The diagnostic assesses the context.
Where AI genuinely fits in HR work and where it does not. We assess use case readiness, not vendor fit. The output is a prioritized list of real opportunities, each scoped to what your function can absorb, with dependencies named. Vendor theater filtered out early.
The flow of HR data through HRIS, ATS, learning, engagement, and adjacent systems, and the gap between that architecture and what AI deployments will demand. A technical assessment, not a vendor inventory. The thread that determines whether the agent you are about to buy has anything usable to work with.
Who owns AI decisions, who owns the people data the models touch, who is accountable when a model affects a hiring, promotion, or pay decision, and whether your posture holds up under EU AI Act, Colorado AI Act, NYC 144, and audit review. AI governance is usually the thread that kills real deployments after the pilot. We assess it before the procurement decision, not after.
Whether the AI agenda is aligned with what HR is actually being asked to deliver, whether the operating model can absorb the change, and where the CHRO sponsorship is real versus performative. The thread that determines whether a successful pilot survives the first leadership change or budget cycle.
The primary activation module is the AI Opportunity Charter. A prioritized list of concrete HR use cases — onboarding automation, case deflection, manager enablement, HR chatbot fine-tuning, agentic workflow design — each one scoped to what your function can absorb, with the dependencies named and the grounding documents built.
Why this is possible
The HR AI market is full of instruments that assess technology. Model benchmarks, vendor scorecards, capability matrices. None of them assess the organization that has to use the technology. That is the gap the Ikona AI Diagnostic was built to fill.
Foundation
The Ikona AI Diagnostic runs the full capture once, through structured stakeholder interviews scoped to your function. The resulting knowledge base becomes the substrate for every subsequent module: a governance charter, an operating model redesign, a business case for a specific deployment. You do not pay to rediscover the organization every time a new AI question arrives.
Calibration
The underlying methodology (the Ikona Systems Diagnostic) was designed by practitioners who ran HR analytics and HR technology at scale. General-purpose AI readiness assessments treat HR as a generic function. We treat it as what it is: a function with its own politics, vendors, regulatory exposure, and pace of change.
Technical bench
Ikona’s technical bench includes founders who built HR science at Expedia and Merck, and ML product at Amazon. They have shipped production systems inside HR contexts, not pilots that stalled. We know what production looks like. We also know what a demo looks like when it is pretending to be production.
Practitioners, not generalists
Co-founder and CEO
Former head of people analytics at Amazon (1M+ employees), JPMorgan Chase, and Google. 20+ years building enterprise analytics functions at scale.
Co-founder and CTO
Former machine learning product leader at Amazon and Expedia. Leads Ikona’s platform and the knowledge store infrastructure that makes the methodology run at scale.
Co-founder and CPO
Built people analytics at Meta, Uber, Nike, and Argo AI, then served as VP of People Analytics Strategy at One Model. HR Tech 100 honoree.
Beyond the three founders
Three founders run every engagement. Behind them is a marketplace of senior people analytics practitioners we pull in when the question demands specific expertise. Compensation benchmarking. Workforce planning at scale. DEI measurement. Specific HCM platforms. Anyone we add has held the role. No analysts billing at partner rates.
We do not pretend to be experts in everything. We know the people who are: compensation, talent mobility, HR tech selection, org design. Every specialist we bring in has done the job at enterprise scale.
Scope expands mid-engagement and the bench expands with it. Scope tightens and we stop billing for bodies you do not need. No new SOW, no renegotiation, no second firm.
Whoever we pull in works from the same structured knowledge store your engagement is building. Nobody starts from scratch. Nobody duplicates questions.
Before you book the call
A baseline you do not capture is a baseline you cannot prove. Deploy AI inside HR before you have assessed current-state readiness and you lose the ability to measure what changed and what is attributable to the investment. Every month you wait is a month of change against a baseline nobody captured.
Those instruments assess the vendor. Eightfold’s scorecard tells you what Eightfold does. HireVue’s tells you what HireVue does. IDC ranks the category. The Ikona AI Diagnostic assesses the HR organization that has to use any of them, and tells you whether your function is ready, what has to be true for a specific deployment to work, and which opportunities are worth pursuing given your governance, data flow, and operating model. You need both kinds of instrument. We are the one that does not exist in your current stack.
Yes, under NDA, on the call. We walk you through anonymized output from a Fortune 100 engagement in the formats your team uses: what a Charter reads like, what the underlying knowledge base looks like, and how provenance back to source conversations is maintained.
We are the discovery layer that makes your HR AI tech stick.
Thirty minutes with a founder. No deck. No pitch. A conversation about your AI portfolio and where the diagnostic fits.
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