Where should you start with AI implementation?
Many organizations have no shortage of ideas for using AI. The harder part is deciding which ideas address a real business problem, can deliver measurable value and are feasible given the current state of data, systems, processes and capabilities.
We do not start by selecting a tool. We connect business objectives with customer, employee and process challenges, then assess data, technology, risk, team readiness and accountability for outcomes.
The outcome is a well-founded decision on the first AI initiative, with a designated owner, KPIs and clear conditions for launch.
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Who is AI Readiness for?
For organizations that recognize the importance of AI but have not agreed where to start, are running isolated experiments without a shared direction, or are considering their first investment in AI tools. -
When should you use AI Readiness?
When there are no shared criteria for selecting initiatives, the readiness of data, systems, processes and teams is unclear, or a budget decision must be made before the conditions for delivery have been validated. -
What does AI Readiness deliver?
The program identifies areas with the greatest potential, reveals barriers before budget is committed, and prepares the first initiative with a value hypothesis, KPIs, an owner and specific conditions for launch.
How can we help?
We take organizations from an unstructured list of ideas to an investment decision based on value, feasibility and readiness to act.
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Setting the direction
We define the expected business outcome, scope, level of ambition and success criteria.
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Identifying areas of value
We connect process challenges and the needs of customers and employees with potential AI applications.
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Assessing organizational readiness
We assess data, technology, processes, risk, capabilities and ownership, and identify barriers that could prevent the initiative from starting.
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Prioritizing initiatives
We compare initiatives using shared criteria for value and readiness.
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Preparing the first initiative
We define the value hypothesis, KPIs, business owner, data, dependencies and conditions for launch.
How the program works
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Set the direction
We start with the business outcome. We define the scope, level of ambition and success criteria.
Decision questionWhat business change should AI deliver?Stage outcomeAgreed scope, objectives and success criteria. -
Identify value
We analyze process challenges and the needs of customers and employees.
Decision questionWhere can AI make a meaningful difference to business outcomes or ways of working?Stage outcomeA map of value areas and an initial set of initiatives. -
Assess readiness
We assess data, technology, processes, risk, capabilities and ownership.
Decision questionCan the initiative be launched now?Stage outcomeReadiness assessment, barriers and conditions for launch. -
Make the decision
We compare initiatives based on value and readiness.
Decision questionWhich initiatives should be launched, prepared or stopped?Stage outcomeA priority portfolio with recommendations. -
Prepare the first step
We define the value hypothesis, KPIs, owner, data and dependencies.
Decision questionWho is accountable for the outcome and how will it be measured?Stage outcomeFirst Initiative Charter.
We start with the business outcome. We define the scope, level of ambition and success criteria.
The deliverables support the decision on where to begin and what must be prepared before launching the first initiative.
What does the client receive?
- AI Value Map: Connects business objectives with process challenges and the needs of customers and employees.
- Priority Portfolio: A list of initiatives with a recommendation to launch, prepare, validate or stop.
- AI Readiness Index: An assessment of data, technology, processes, risk, people and ownership.
- First Initiative Charter: Value hypothesis, KPIs, owner, data, dependencies and conditions for launch.
From an AI discussion to an actionable decision
A valuable initiative must address a business problem, be feasible to deliver and have an owner accountable for the outcome. We do not create a catalog of possibilities or rank tools. We structure the evidence needed to make an investment decision.
Why Grant Thornton?
Building a repeatable capability to scale AI requires combining value and portfolio management with the design of the operating model, standards, architecture, and team ways of working.
Grant Thornton
The Grant Thornton team supports the design of the portfolio management model, accountability, decision rights, investment criteria, and value measurement system.
Digital team | EDISONDA
Grant Thornton’s Digital experts translate the scaling model into shared principles for delivering initiatives, addressing user needs, and managing processes, data, technology, and capabilities.
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30 years+
operating in Poland
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1200+
employees across 7 offices
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2400+
satisfied Grant Thornton clients each year
