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AI Opportunity Discovery

Find Out Where AI Can Actually Help Your Business

Most teams know AI could help somewhere, but not where to start. We scan the business department by department, list the real use cases, and rank them by value and effort. You get a clear picture of the quick wins and the bigger bets.

50+ ERP and software projects. Zero failed projects since 2021.

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Value vs effort: sample opportunity map
Value
Quick wins
Invoice OCR Payment follow-ups
Big bets
Demand forecasting
Nice to have
FAQ replies
Park for now
Full chatbot
Effort
2 wk
Typical engagement
6
Departments scanned
1
Ranked opportunity list
0
Guesswork on where to start
Why It Matters

The hardest part of AI is knowing where to start

The technology is ready. What most teams lack is a clear, ranked view of which problems in their own business are worth solving with AI first.

Start From the Business

We start from your friction, not from the technology

The wrong way to adopt AI is to pick a tool and look for a use. We do the reverse. We look at where your teams lose hours, re-key data by hand, or wait on slow manual steps, then match AI to those problems.

  • Where time and effort leak in each department.
  • The manual work that repeats every day.
  • The problems AI is genuinely a good fit for.
A team mapping business problems on a board
Quick Wins First

We find the high-value, low-effort wins before the big bets

Every idea is ranked by the value it creates and the effort to deliver it. That puts the quick wins at the top, so you can show a result early, build confidence, and then take on the larger projects with proof behind you.

  • Each opportunity scored on value and effort.
  • Quick wins you can start on right away.
  • Bigger bets planned for later, with eyes open.
Ranking opportunities by value and effort
What We Surface

The kind of opportunities we surface

Real, concrete use cases from across the business, each tagged with the value it creates and the effort it takes. These are examples, your list is built around your own operation.

Invoice data capture
Read supplier invoices automatically and post them to the ledger, instead of typing each one by hand.
High value Low effort
Payment follow-ups
Draft and schedule reminder messages for overdue invoices, so finance chases fewer of them by hand.
High value Low effort
Sales lead triage
Score and sort incoming enquiries so the sales team spends its time on the leads most likely to close.
High value Medium effort
Customer reply drafting
Draft first-response replies to common support questions, ready for an agent to review and send.
Medium value Low effort
Purchase order matching
Match orders, receipts and invoices automatically and flag only the mismatches for a person to check.
High value Medium effort
Demand forecasting
Predict stock and demand from past sales, so procurement orders the right amount at the right time.
High value High effort
How It Works

From first call to a ranked opportunity list in about two weeks

1
Discovery call
We meet your team and understand your goals, priorities and where the pain is felt.
2
Department scan
We work through finance, sales, operations, procurement, HR and customer service.
3
List use cases
We write down every candidate AI use case we find, in plain business terms.
4
Rank by value and effort
We score each idea, so the quick wins and the bigger bets are clear to see.
5
Readout
We hand over the ranked list and walk you through where to start and why.
What You Get

A ranked list you can act on, not a slide deck

🔍

Opportunity long list

Every candidate AI use case we found across your departments, written in plain business language.

📈

Value and effort ranking

Each idea scored on the value it creates and the effort to deliver, plotted so priorities are obvious.

⚡

Quick-win shortlist

The high-value, low-effort ideas you can start on now to show a result early and build momentum.

🎯

Bigger-bet shortlist

The larger opportunities worth planning for, with a clear note on what they would take.

📝

Use-case one-pagers

A short summary of each top opportunity: the problem, how AI helps, and the likely payoff.

🔑

A clear starting point

A straight answer to the question "where do we even start with AI", backed by your own numbers.

Why Discover First

What a discovery engagement changes

Clear
View of where AI fits
Ranked
Opportunities, not a wish list
Quick
Wins you can start now
Focused
Spend on what pays back
Aligned
Teams agree on priorities
Confident
Decisions backed by evidence
Why Us

Why teams choose TCB Infotech for AI opportunity discovery

1
We know the systems
We build ERP and software, so we read your real data and stack, not a generic checklist.
2
Business first
We start with your operation and where it leaks time, then look at AI, not the other way around.
3
Honest ranking
If an idea is not worth it yet, we say so and tell you what to park for later.
4
Practical use cases
We favour the boring, high-value automations that pay back over the flashy ones that do not.
5
No lock-in
The opportunity list is yours to run with any partner or your own team.
6
Proven delivery
50+ projects across industries, with zero failed projects since 2021.
FAQ

AI opportunity discovery questions

What is AI opportunity discovery?
It is a short advisory engagement that looks across your departments, lists where AI could help, and ranks each idea by value and effort. You end with a prioritized list of AI opportunities you can act on, starting with the quick wins.
How is this different from an AI readiness assessment?
Readiness checks whether your data, systems and team are ready for AI. Opportunity discovery answers a different question: where in the business should you use AI at all. Many companies run discovery first to find the ideas, then check readiness on the ones they want to pursue.
Do you start from the technology or the business?
We start from the business and its friction. We look at where teams lose time, re-key data or wait on manual steps, then match AI to those problems. We do not start with a tool and look for a use for it.
How long does the engagement take?
A focused discovery usually runs about two weeks, depending on how many departments and systems are involved. It ends with a ranked opportunity list and a short readout.
Will you try to sell us a build at the end?
No. The output is a ranked list of opportunities that is yours to keep. You can act on it with any partner or your own team. This is advice, not a sales pitch for a project.
Which departments do you look at?
Typically finance, sales, operations, procurement, HR and customer service. We adjust the scope to your business and focus on the areas where the friction and the potential return are highest.

See Where AI Fits in Your Business

Book a free consultation. We will talk through your departments and where the friction is, and show you what an opportunity discovery would surface for your business.

Book a Free Consultation →

No commitment. A practical first look at where AI can help.

AI Opportunity Discovery Features

What Is Inside an AI Opportunity Discovery

The engagement is a working scan of your business, not a survey. Here is what we look at, how we rank what we find, and what you walk away with.

Core Features

From a department scan to a ranked list you can act on

Department by Department Scan

We look across the whole business, not one corner of it

We work through finance, sales, operations, procurement, HR and customer service, and talk to the people who do the work. That is how we find the friction that a top-down view would miss.

  • Every core department covered, not just IT.
  • Conversations with the people doing the work.
  • The manual, repeating tasks written down.
A discovery workshop across business departments
Use-Case Long List

We write down every candidate use case we find

Each opportunity is captured in plain business terms: the problem, the team it affects, and how AI would help. Nothing is filtered out at this stage, so you can see the full picture before we rank it.

  • Opportunities described in plain language.
  • The problem and the team behind each one.
  • A complete view before anything is cut.
A long list of candidate AI use cases
Value and Effort Ranking

We rank the list so the quick wins rise to the top

We score each idea on the value it creates and the effort to deliver, then plot them on a simple value versus effort map. The high-value, low-effort ideas become your quick-win shortlist.

  • Every idea scored on value and effort.
  • A clear value versus effort map.
  • A quick-win shortlist to start with.
Ranking AI opportunities on a value and effort map
What You Get

Everything the engagement delivers

🔍

Opportunity long list

Every candidate AI use case we found across your departments, in plain business language.

📈

Value and effort ranking

Each idea scored on value and effort and plotted on a simple map, so priorities are obvious.

⚡

Quick-win shortlist

The high-value, low-effort ideas you can start on now to show a result early.

🎯

Bigger-bet shortlist

The larger opportunities worth planning for, with a clear note on what they would take.

📝

Use-case one-pagers

A short summary of each top opportunity: the problem, how AI helps, and the likely payoff.

🧩

Vendor-neutral plan

A list you own and can run with any partner or your own team, with no lock-in.