Ambition Has Outpaced Value Realization
Enterprises are not short of AI ambition. They struggle to convert it into value, and the issue is rarely the technology. Most AI strategies stop too early, naming use cases without the decisions AI will improve, projecting value without connecting operational impact to financial result, and launching pilots without designing the change required to scale.
1 in 4
AI initiatives meet revenue impact expectations
$1.3M
average spend of each AI use case
ISG grounds AI strategy in what AI is actually delivering - based on experience across 2,400 enterprise use cases - then aligns investment to where impact is proven. We identify where AI can create measurable value, define what must change to capture it, design the transformation and hold value realization to evidence.
The Value Gap
Most AI strategies stop before value is realized. A strong strategy should answer questions most organizations still cannot:
Which decisions and workflows will AI actually improve, and by how much?
What must change across data, process and the operating model to capture that value?
What is the evidence that value is being realized, not just projected?
Which initiatives should be funded, paused or stopped?
As AI portfolios grow, four failure patterns recur.
Use Cases Without Decision Analysis
Use cases are hypothesis until they are tied to the specific decisions, workflows and actions where AI improves performance. Most strategies never make that link.
Technology Without Change Architecture
AI value depends on more than models and platforms. It requires changes to process, roles, decision rights, incentives and adoption. Deploy the technology without designing the change and the value is left stranded.
Value Claimed but Not Evidenced
Projected ROI is not value. Enterprises need a measurement path from system performance to adoption, operational impact, business outcome and financial result. Without it, funding rests on assertion.
Pilots That Do Not Scale
A successful pilot does not prove an initiative can scale. Scaling requires governance, workforce readiness, operating model alignment and sustained executive ownership. The barrier is organizational, not technical.
A Disciplined Path from Opportunity to Value
AI strategy is not a vision exercise. It’s a value-realization discipline that must function across the enterprise. We connect strategy, business case, transformation design and value realization into one lifecycle. Enterprises enter at the point that matches their maturity.
Find where AI can create enterprise value.
We identify where AI improves performance, reduces cost, increases speed, raises quality or reduces risk.
The output is a prioritized, investable set of opportunities.
This includes:
- Decision-level analysis of where AI changes how work is performed
- A prioritized opportunity set with a clear value thesis for each
- A readiness view across data, process and operating model
- A defined path into business case development
Build the case, then design the change required to scale.
We translate opportunities into decision-ready business cases, then convert approved investment into an executable transformation roadmap.
We turn your approved investment into a roadmap that scales. Not another isolated pilot.
This includes:
- Investment-grade business cases defining cost, value, risk and measurement requirements
- The change required across data, technology, process, decision rights, workforce, culture and partner ecosystem
- A sequenced roadmap with workstreams, owners, governance forums and adoption plans
- Sourcing and build-versus-buy decisions grounded in provider intelligence
Prove value is landing, and intervene when it is not.
We track whether AI initiatives are producing the intended value across adoption, operational performance, business outcomes and financial realization.
Value does not appear when a model goes live. It is designed, measured and managed.
This includes:
- A defined value path from system performance to financial result
- Tracking across adoption, operational impact and business outcome
- Evidence discipline that connects each step for executive confidence
- Intervention points when value is not materializing
How ISG Helps
ISG helps enterprises design and operationalize pricing models built for Al-enabled service delivery. We bring depth in benchmarking, sourcing, provider ecosystems, contract design, governance and Al advisory.
Pricing Framework Design
Conventional models price volume, not autonomy. A model matched to your service portfolio and provider landscape that closes the gap, with autonomy levels defined, resource units mapped and value tracking built in.
Contract and SLA Integration
A pricing model changes nothing until it reaches the contract. Built into your service levels and performance terms, it makes price reflect execution maturity, oversight, risk ownership and accountability.
Intelligent Pricing Operations
Price set once falls behind as autonomy advances. A repeatable operating model keeps it current across sourcing, supplier governance and performance management, so value is measured and risk managed as Al matures.
