Find out why AI productivity gains in IT services fell short, and what is being changed

For COOs, delivery heads and investors who need a clear account of where AI productivity did and did not land, and how providers are recalibrating.

Engagement type: Team Pod
Experts: 3 consulted · 1 lead
Hours: ~40
Duration: 3 weeks

What the client needed

A firm needed to understand why the AI-driven productivity and cost expectations set in 2023–24 had not fully materialised by early 2026: where the gaps emerged across the software lifecycle, customer experience, finance, IT service management and talent; how the industry is recalibrating — revised estimates, extended timelines; what providers are changing in governance, workflows, talent models and operating mechanisms to make gains measurable and durable; and what that means for headcount, delivery models and pyramids.

The experts engaged

Previously at HCL Technologies · 23 years

Roles heldgeneral manager, IT infrastructure management, service delivery and end-user computing

Led AI and automation enablement across large managed-services accounts
Owned productivity commitments and their measurement with clients

Atlas Verified · Tier B

Previously at HCL, Sopra Steria · 25 years

Roles heldAGM, ITSM and digital services · global service delivery manager, ITSM and digital transformation

Delivery operating-model redesign for AI-assisted service management
Productivity programmes across second- and third-generation outsourcing deals

Atlas Verified · Tier C

Previously at Philips GCC, Teva, Carrier · 19 years

Roles helddirector, finance at a global capability centre · associate director, finance · head of finance and treasury

Captive-side owner of AI productivity cases in finance operations
Measured realised versus promised savings over three budget cycles

Atlas Verified · Tier B

A exceptional · B strong · C competent — the tier is derived from the whole assessment, not a single score. The transcript and report are open to you before you engage. How verification works →

The brief

The questions on the table

As the client wrote them, lightly shortened. Client and respondents are not named.

Q1
Why did the 2023–24 productivity and cost expectations not materialise, and where exactly did the gaps appear?
Q2
How are expectations being recalibrated — lower estimates, longer timelines, different metrics?
Q3
What are providers changing in governance, workflows, talent and operating mechanisms to make gains stick?
Q4
Are fewer people really needed for the same work, and where is that showing in pyramids and delivery models?

The hours

What the work involved

01
Gap analysis
Expected versus realised gains by area — SDLC, CX, F&A, ITSM, change — with the reasons the lead saw from inside a provider’s AI enablement programme.
02
Recalibration
How targets, timelines and measurement were reset in 2025–26, and what the new commitments to clients look like.
03
Operating changes
Governance, workflow redesign, talent models and incentives that providers are putting in place, with what is working.
04
Cross-check
Two delivery leaders and a finance leader from captive and provider organisations reviewed the headcount and pyramid conclusions.
05
Working session
With the client’s operations leadership.

Deliverables

What the client received

Gap analysisBy area, with causes.
Recalibration noteTargets, timelines, measurement.
Operating-change catalogueWhat providers are doing.
Headcount and pyramid viewWhere fewer people are actually needed.
One working sessionWith notes.

The terms

What an engagement like this costs

You buy hours in blocks and can change the expert at the end of any block, at no extra cost. Longer projects run in stages: pause after a block, pick up the next stage when you are ready.

Pricing in full →

Rate band: $65–$250 /hr; Senior specialists can be up to $500
Hour blocks: 1 · 2 · 5 · 10 · 20 · 50 · custom
This engagement: Team Pod · ~40 hours · 3 weeks

Resetting your AI productivity case?

Describe what you need

For example: “Our board wants to know why the AI savings we promised in 2024 are not in the numbers, and what to commit to now.”

We aim to come back with matched experts within 24 to 72 hours.