Problem before technology
Separate the desired outcome from enthusiasm for a technology. Automating an activity does not by itself demonstrate customer value.
AI Investment Prioritization
Where should your company really invest in AI?
Before approving a pilot, identify the problem AI should solve and how you will measure the improvement.
Before scaling pilots or buying technology, examine the customer or business problem behind each proposal and whether it justifies the resources required.
For CEOs, CIOs, CTOs, CFOs and innovation and operations leaders.
AI investment starts with a business choice.Which application deserves resources before implementation scales?
How teams made their choices
- 500+Companies served by George Eich
- 650+Startups mentored through Startup SC
- 60+Startups supported through Cubo Itaú
Companies George Eich has worked with
- Techne
- Climoo
- PSA
- Ambev
- Evous
- Locates
Institutions and startup programs
- Sebrae
- ACATE
- MIDITEC
- Cubo Itaú
- Startup SC
EVOUS
The team used customer evidence to decide when to strengthen its core product and when to expand its offering.
Locates
While switching platforms, the team used customer needs to decide which features to include and which to defer.
“We gained a more strategic view of the product and were able to prioritize the roadmap and the company’s positioning.”Feedback shared with the Institute · English translation
George Eich InstituteDirection for the choice. Evidence for the decision.
500+companies advised by George Eich
10+ yearsof experience in strategy and execution
3 to 6 weeksreference for research and executive analysis, depending on scope
When priorities compete for capacity
AI opportunities multiply. Your capacity does not.
Sales wants an assistant. Operations wants automation. Product wants AI features. Leadership wants visible progress. Pilots move forward in parallel, each with its own promise. The missing decision is which problem deserves to be solved first.
Leadership
“We need to show progress in AI.”
Technology
“Which use case should we implement first?”
Operations
“Will this remove a real bottleneck?”
Finance
“What justifies the next investment?”
A technically successful pilot can still be a weak priority. Before selecting tools or expanding adoption, the company needs to choose where AI can make a relevant contribution.
Business relevance before implementation
Start with the problem that deserves to be solved.
An AI application should have a clear place in the business agenda. Before adding tools, integrations or new routines, decide which need deserves attention and what would justify the investment.
The cost of priorities without a clear foundation
More AI initiatives can create more cost without more value.
The risk is committing capital, people and technology to priorities that add effort and complexity without increasing the company's ability to create and capture value.
Pilots without a clear direction
Experiments consume funding and leadership attention without resolving which applications deserve to advance.
New operating commitments
Data preparation, integrations, vendors and maintenance add costs the company must sustain.
Capacity diverted from the business
Teams spend time on applications whose relevance has not been compared with other priorities.
Support for your next decision
Choose the AI opportunity before scaling the investment.
The Study investigates the needs behind the options before priorities are ranked. The company and the Institute define the decision, customer groups and scope; findings inform resource allocation.
Customer and operational evidence
Investigate shared customer relevance when the application changes the offering; use process evidence when the decision concerns internal efficiency.
Adoption and feasibility
Assess quality, costs, risks and expected adoption. Relevance guides where to investigate before committing resources to AI.
Help me prioritize AI investments
Bring the decision your company needs to make.
Priorities with a clear foundation. Guidance for the next choice.
An executive interpretation that connects evidence to the decision your leadership needs to make. The deliverables reflect the agreed business context and scope.
A clear focus for AI investment
The problems, use cases and opportunities that deserve priority in the current business context.
Evidence and open questions
The reasons supporting each choice and the assumptions that still need validation.
Guidance for the initiative portfolio
What to advance, investigate further, defer or remove from the current investment agenda.
Specific deliverables are defined according to the decision and the agreed scope.
When to apply
Before the next round of decisions.
Allocate an AI investment budget
When leadership has funding available but competing applications have not been compared.
Decide what to scale
When experiments have produced outputs but their business relevance remains unclear.
Choose where to automate
When several workflows could use AI and the company needs to choose where to focus.
Decide before selecting a solution
When vendors or platforms are being considered before the business priority is clear.
About ai investment prioritization.
What is AI investment prioritization?
It is the decision about which AI use cases, initiatives and investments justify company resources. It connects potential applications to relevant business needs and makes clear what should advance, what needs validation and what should wait.
Does the Institute implement AI solutions?
This engagement focuses on choosing where to invest and which initiatives deserve priority. Any technical implementation requirements are defined separately according to the scope and capabilities needed.
Is this useful if we already have AI pilots?
Yes. Existing pilots can be part of the decision about what to continue, validate, scale or stop. A functioning application alone does not establish that it deserves priority.
What does the company receive?
An executive interpretation connecting the evidence to the decision your leadership needs to make. A clear focus for AI investment: The problems, use cases and opportunities that deserve priority in the current business context. Evidence and open questions: The reasons supporting each choice and the assumptions that still need validation. Guidance for the initiative portfolio: What to advance, investigate further, defer or remove from the current investment agenda. Specific deliverables are defined according to the decision and the agreed scope.
How long does the engagement take?
The reference is 3 to 6 weeks for structured research and executive analysis, depending on the scope. Timing depends on the decision, access to information and participant availability. The first conversation helps assess the appropriate format.
Which AI initiative deserves your next investment?
Tell us which AI opportunities are competing for resources. We will assess how to help your leadership choose where to focus.
Help me prioritize AI investmentsRequest a conversation with the George Eich Institute.
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