- A global report informs the context; your project portfolio depends on your own operations.
- Compare use cases by expected value, available data and integration effort.
- A useful pilot should enable an explicit decision, with an owner and defined criteria.
What the report helps explain
Stanford’s AI Index 2026 brings together evidence on AI capabilities, the economy, education and governance. Among other findings, it highlights uneven performance across tasks. The report’s publication date must be distinguished from the period covered by each indicator. This overview helps frame questions; it does not replace an examination of a company’s operations.
We suggest turning this reading into a portfolio of decisions. Leadership should be able to explain why a project has priority, what assumption it tests and what evidence might lead to stopping it. This makes the AI programme understandable to business teams, IT and procurement.
Start with an observable problem
Avoid broad labels such as “AI for customer service”. Describe a situation instead: advisers search for a procedure across several systems, a team reformats documents manually, or salespeople prepare meetings using scattered sources. Identify the user, how often the work occurs and the consequences of an error.
Collect a small set of real examples for each situation. How many steps are required? Where does rework happen? How much time is spent searching, entering information or checking results? These observations establish a baseline. They can also reveal a problem rooted primarily in organisation or data quality.
Compare value and the conditions for success
We recommend a short decision matrix. Value may come from a shorter turnaround, more accessible information, better preparation or a newly possible service. Feasibility depends on sources, access, systems to connect and the ability to check outputs. Adoption depends on the people who will need to change their habits.
Weights should reflect your context. Finance may place greater emphasis on traceability; a product team may prioritise learning speed. A score makes the discussion explicit. It does not turn a weak estimate into a precise measurement. A blocking constraint must remain visible even when the total score looks high.
Choose a pilot that enables a decision
A pilot should be narrow enough to evaluate and representative enough to teach you something. A knowledge assistant might begin with one family of approved procedures and a defined user group. The test set should include ordinary questions, ambiguities and cases where the assistant should refrain from answering.
Define possible outcomes at the outset: expand, make targeted corrections or stop. Specify who decides and on what evidence. A successful pilot may reveal that source material needs correction or a process needs simplifying first. That conclusion is valuable if it prevents scaling a solution that merely moves the difficulty elsewhere.
Build a balanced portfolio
Separate improvements accessible in the near term, necessary foundations and more uncertain explorations. The first group produces early learning. Foundations enable later projects: document quality, identity, APIs or usage rules. Explorations test a new way of working without immediately committing the whole organisation.
The review group should examine changed assumptions, observed outcomes and resolved dependencies. To prepare a discovery call, bring three concrete problems, the relevant tools and the people who know the process. That is a more actionable starting point than a long list of technologies to purchase.
| Criterion | Discovery question | Evidence to collect |
|---|---|---|
| Value | What work do we want to improve? | Examples, frequency and baseline |
| Data | Are sources accessible and reliable? | Inventory, owner and permissions |
| Integration | Which systems must work together? | Flows, APIs and dependencies |
| Adoption | Who will use and verify the solution? | Business owner and pilot users |
| Decision | What would justify expansion? | Quality, cost and usage criteria |
Sources & methodology
This insight combines cited publications with editorial analysis. Illustrative examples are not client results. Vendor features and terms may change.