01
Use cases lack a business baseline
Teams describe a possible AI feature without the current cost, delay, error or revenue measure.
An AI strategy should end with funded decisions.
A useful engagement chooses the business priorities, tests the use cases, sets the operating rules and leaves leaders with a roadmap they can fund.
Business prioritiesFunded roadmapNamed owners
AI strategy consulting
Leaders should receive four usable outputs
01
Business and capability baseline
Current state02
Prioritised use-case portfolio
Choices03
Operating and governance model
Rules04
Funded 12-month roadmap
ActionEvery recommendation has an owner and next decisionExecutive pack
- AI strategy consulting
- AI strategy consulting helps an organisation decide where AI can create value, which work to fund and what people, technology and controls that work requires.
The engagement should connect company priorities to a small portfolio of use cases, a delivery and governance model, clear investment choices and a dated roadmap. It should also identify the work the company should defer or stop.
Why strategy work stalls
A long list of ideas does not guide investment.
Leaders need comparable evidence, clear choices and owners. Workshops without those outputs tend to create more activity without resolving the funding question.
02
Technical choices arrive too early
A model or platform decision shapes the programme before the team has defined the job and success measure.
03
Governance sits outside the roadmap
Privacy, security, testing and human review appear as late approval tasks instead of planned work.
04
No one owns the next decision
The strategy ends with themes and options while funding, owners and dates remain open.
Required deliverables
Ask for decisions, records and a sequence.
The consultant’s output should be usable by the leaders and delivery teams who continue the work after the engagement.
Starting point
Business baseline
Record the company priorities, process measures, current initiatives, spend and constraints.
Priorities
Use-case portfolio
Score each candidate on value, feasibility, data, risk, adoption and time to evidence.
Architecture
Technology position
Set principles for approved platforms, build and buy choices, data access, evaluation and cost.
Controls
Governance model
Define risk tiers, decision rights, control paths, records and the review cadence.
Ownership
People plan
Name executive sponsors, business owners, delivery roles, training needs and internal capability gaps.
Action
Funded roadmap
Sequence the next 12 months with owners, costs, milestones, evidence gates and stop conditions.
Partner selection
Choose a partner by the work they can prove.
A strong partner can connect executive choices to delivery details and can explain where the client team must retain authority.
| Question | Good evidence | Warning sign | Why it matters |
|---|---|---|---|
| How will you prioritise? | A clear scoring method using client data | A workshop vote or generic trend list | Funding needs comparable evidence |
| How will you test feasibility? | Representative data, system and process constraints | Vendor demos alone | Delivery limits change the business case |
| How will you handle governance? | Risk tiers, owners, controls and records | A policy added at the end | Controls affect scope and timing |
| What remains after the project? | Roadmap, owners, templates and decision cadence | A presentation without working records | The client team must continue the work |
Typical engagement
Move from evidence to executive decisions.
The duration depends on company size and access to data. The phases should remain clear even when the calendar changes.
01
Frame
Set the decision scope
Agree the business questions, executive sponsor, teams, evidence and decisions the engagement must support.02
Assess
Build the baseline
Review processes, use cases, data, systems, skills, controls, spend and current delivery.03
Choose
Compare the options
Score the use cases, test key assumptions and prepare the investment and operating choices.04
Commit
Issue the roadmap
Assign owners, funding, milestones, governance gates and the next executive review dates.Related decisions
Continue with the part you need.
These pages cover the owner, starting point and India-specific context around this guide.
Questions leaders ask
Practical answers
How long does an AI strategy engagement take?
A focused engagement can take four to eight weeks. A larger enterprise review can take longer when it spans several business units, countries or control functions. The scope should name the decisions and evidence required rather than promise a fixed calendar for every company.
What does AI strategy consulting cost?
Partners may price a fixed discovery, a milestone-based project or monthly advisory work. Compare the scope by people involved, evidence collected, use cases tested, deliverables, decision support and follow-through. A low fee can still be expensive if the output does not support funding or delivery.
Should the strategy include implementation?
The roadmap should include delivery requirements, costs, owners and evidence gates. The same partner may support implementation under a separate scope. Keeping the work packages clear helps leaders compare cost, ownership and performance.
Who should sponsor the engagement?
Use an executive sponsor who can bring business, technology, finance and control teams into the same decisions. The sponsor should also have the authority to assign owners and take the final roadmap into the funding process.
Set the decision scope
Build a strategy the company can fund and run.
Bring the current initiatives, business priorities and open executive questions. Gyde will shape the engagement around the decisions they require.