SIS International  |  AI Enablement

SIS AI Solutions Training Program

The invoice is exact, to the cent. The return is a story your CFO cannot sign. SIS closes that gap. We build the layer between the model you bought and the result you were promised: governance, adoption, and measurement.

0 yrs
Turning evidence into decisions for senior leaders
0%+
Of the Fortune 500 served
0+
Countries, across 50+ industries
The problem, named

Spend is tripling. The return is missing.

Every board is asking the same question, and almost no one can answer it: where is the return on AI? The cleanest numbers in the field all point at the same hole. Money is going in. A result a finance team can sign is not coming out.

39%
of executives could attribute any enterprise-level EBIT impact to their use of AI. Of those who could, most said it was under 5% of EBIT.
McKinsey, State of AI 2025, self-reported attribution survey of perception, not an audit.
~$37B
estimated US enterprise spend on generative AI in 2025, up from roughly $11.5B the year before. More than triple in a single year.
Menlo Ventures estimate, single source, US only, excludes chips and cloud. Direction, not audited fact.
64%
of CEOs invest before they clearly understand the value, driven by the fear of falling behind. Only 25% said AI delivered the return they expected.
IBM 2025 CEO study, a vendor survey, which makes the unflattering numbers an admission against interest.
~95%
of organizations saw no measurable P&L effect from custom GenAI pilots over a short window. The cause cited was a learning gap, not weak models.
MIT NANDA 2025, single-sourced, limited sample, method challenged. "No measurable effect" is not "failure."

The problem is not the model. The models work. The problem is the layer nobody builds: governance, adoption, and measurement. None of it demos at purchase time, which is exactly why the money skips it, and exactly why the return never shows up.

Find your own spend-to-value gap

Move the slider to your annual AI spend. The figures below are drawn from the studies above, they describe where most organizations actually land today, before the enablement layer is built.

$2.0M
$1.2M
Spend with no attributable EBIT impact, at the McKinsey 61% rate
~95%
Chance a custom pilot shows no measurable P&L effect without the enablement layer
1 layer
Governance, adoption, measurement: the difference between the two figures on the left
The reframe

AI is a capability you build around, not a product you buy.

A model is an input. A capability is an outcome. You can own every input and still have no capability at all. That shift changes four decisions:

What you fund

Integration, change work, and people, not just licenses and seats.

Who owns it

You staff a capability. You only sign a purchase.

How you measure

The outcome a finance team can find, not adoption dashboards full of green.

What you ask vendors

Not "what can your model do," but "which layer is this, and how much will you actually build for me."

What SIS offers

Enablement, not theater.

The program comes in four formats, sized to where you are.

Executive briefing

A focused session for a leadership team. We teach the spend-versus-value gap, name the missing layer, and leave you with the language to ask the right questions of your vendors and your own teams.

Workshop

A working session that takes one real use case through the spine. Your people leave with a draft governance baseline and a one-page brief, not a deck.

Advisory engagement

Hands-on support across the full lifecycle, from governance design through adoption and measurement, sized to your organization.

AI governance & readiness assessment

An evidence-disciplined review of where your AI footprint sits today, which named risks touch which systems, and where the enablement layer is missing.

A client leaves an SIS engagement with four things in hand

  • A governance baseline built on the NIST AI RMF, with a named owner and a mapped risk list.
  • An adoption plan organized by persona, so the new way becomes the easier way for the people who do the work.
  • A measurement model a CFO will trust, built on a dated baseline and honest attribution.
  • A 90-day plan where every item has an owner, an artifact, and a date.
The curriculum

The enablement layer is a spine you can teach, own, and fund.

SIS teaches it as eight modules, governance first, across the full lifecycle. Tap any module to open it.

0

The floor: AI literacy

+

Learn what a token is, how to prompt, what responsible use means. Then understand the trap: literacy is the floor, not the building. A literate workforce with no governance, no adoption plan, and no measurement is a literate workforce watching the same pilots stall.

A literate workforce, and the knowledge that the certificate is an input, not an outcome.
1

Governance as the spine

+

Governance is misunderstood as a brake, so nobody funds it. Replace the picture. Governance is a spine: the frontier moves, and governance is what makes the model replaceable. We build it on the NIST AI RMF (Govern, Map, Measure, Manage) so your operation scales without breaking when the best model changes.

A governance backbone that makes the model replaceable.
2

AI security as governance

+

The second face of governance, not a bolt-on. Risk arrives named and numbered on the OWASP Top 10 for LLM Applications. A vendor can patch a CVE on their servers. A vendor cannot map your footprint, own your control map, or set your risk appetite, that lands inside your building, with your data, under your name.

An owned control map drawn from the OWASP Top 10 and the NIST loop.
3

Adoption is the product

+

Provisioning a seat is the easy half. The value lives in the redesigned work around the license, never in the license itself. A tool nobody uses returns zero. We build a persona-based plan that makes the new way the easier way for the specific people who do the work.

A persona-based plan that makes the new way the easier way.
4

Measure what matters

+

This is the layer that lets you stand before a board and say what the money bought, in language it accepts. We measure real output against a captured, dated baseline, with a control. A number reported without a baseline is an opinion, and a finance leader will treat it as one.

A measurement model with a dated baseline a CFO trusts.
5

Build, buy, or partner

+

The real decision is who owns and funds the enablement layer for the next three years. We use the taker-shaper-maker frame, score every vendor on one rubric where fit and governance carry nearly half the weight, then apply the hard disqualifiers a demo hides: SOC 2, data residency, model cards, IP indemnification, a time-boxed pilot.

A scored sourcing decision with hard disqualifiers and a TCO model.
6

The operating model

+

Hub-and-spoke becomes a bottleneck the units route around. Pure federation fragments into seven vendors and seven private definitions of "approved." The working answer is one strategy, many builders, governed centrally. The center owns the rules and the visibility (the standard, the registry, the audit trail) not the keyboard.

One strategy, many builders, governed centrally.
7

Your first 90 days

+

The sequence is small on purpose. Thirty days to see clearly. Thirty to build the spine. Thirty to prove or kill one thing. Every item has an owner, an artifact, and a date. If an item produces no artifact, you did not do it.

A 30-60-90 plan where every item has an owner, an artifact, and a date.
The curriculum at a glance
ModuleThe executive question it answersThe outcome it produces
0 · The FloorDoes my organization understand the basics?A literate workforce, and the knowledge that literacy is the floor, not the building
1 · GovernanceHow do I move fast without breaking delivery when the model changes?A NIST-based governance backbone that makes the model replaceable
2 · SecurityWhich named risks touch which systems, and who owns each?An owned control map drawn from the OWASP Top 10 and the NIST loop
3 · AdoptionWhy is a tool we paid for sitting unused?A persona-based adoption plan that makes the new way the easier way
4 · MeasurementWhat did the AI money actually change on the income statement?A measurement model with a dated baseline that a CFO trusts
5 · SourcingWho owns and funds the layer between the model and the result?A scored sourcing decision with hard disqualifiers and a TCO model
6 · Operating ModelWhere does the AI function sit, and who governs it?One strategy, many builders, governed centrally
7 · First 90 DaysWhat do I do on Monday?A 30, 60, and 90 day plan where every item has an owner, an artifact, and a date
Why SIS

The discipline AI enablement has been missing.

SIS International Research was founded in 1984 and is headquartered in New York City. For 42 years we have done one thing with discipline: turn evidence into decisions for senior leaders. That is what separates an enablement partner from a vendor selling you the next model.

1984
Founded in New York City
0%+
Of the Fortune 500 served
0+
Countries, 50+ industries
Who this is for

The people who decide where the AI money goes.

You do not need to explain a transformer or know what a token costs. Governance, adoption, and measurement are ordinary management discipline pointed at a new capability.

CEOs

Tired of approving the invoice and waiting for the return.

COOs

Own the operating model and the question of where the AI function sits.

CFOs

Need a number they can defend in the second meeting, not just the first.

Heads of strategy

Set the direction once, in the center, and want it to hold.

Transformation leads

Own adoption and know that a tool nobody uses returns zero.

You have bought the input. Now build the ability to use it.

The hard part was never the model. Let us help you build the part that pays.