# Getting ready for AI: *knowing where to begin*#

Which opportunities are genuinely worth pursuing? Is the organisation ready for them? And what needs to be in place before moving forward?

This article takes a closer look at the **Advisory & Readiness** part of our approach to organisational transformation with AI.

AI has opened up a wide range of possibilities for organisations. From helping people find and work with information to supporting decisions and automating parts of workflows, there are many places where AI could potentially play a role.

The harder question is often **where to begin**. Which opportunities are genuinely worth pursuing? Is the organisation ready for them? And what needs to be in place before moving forward?

Getting ready for AI starts with answering these questions before deciding what to build.

## Understanding Where the Organisation Is Today#

Before deciding where AI could help, we first need to understand **how the organisation works today** — how work moves across teams, where knowledge lives, which systems people depend on, where decisions and handoffs happen, and what the organisation is trying to improve.

Consider a business. A customer requirement might begin in a sales conversation, get captured in the CRM, appear again through support, and eventually reach the product team. The knowledge needed along the way may be spread across documentation, support tickets, different systems and people's experience.

Looking at the organisation this way helps us understand **how its people, knowledge, systems and workflows connect**, as well as where the friction and opportunities for improvement lie.

With that picture in place, we can start asking: **where could AI meaningfully help?**

## Identifying Where AI Could Help#

Once we understand how the organisation works, we can start looking for places where AI could make a meaningful difference. This might mean helping people access knowledge more easily, reducing repetitive work, supporting decisions, or enabling new ways of getting work done.

For a business, this could reveal opportunities to help sales teams prepare for customer conversations, help support teams find relevant product knowledge faster, or help product teams bring together customer feedback from different sources.

At this stage, the goal is to **identify the possibilities**, not yet decide which ones should be pursued.

## Prioritising the Opportunities#

Identifying opportunities is only the beginning. The next question is **which ones are worth pursuing first**.

We can look at each opportunity in terms of the value it could create, how feasible it is to implement, the risks involved, and how well it aligns with what the organisation is trying to achieve.

For a business, improving access to product knowledge for support teams might have an immediate impact on resolution time and be relatively straightforward to test. Other opportunities may offer value but require greater changes to systems, processes or ways of working.

Prioritisation helps the organisation focus its attention on the opportunities that are **both valuable and practical to pursue**.

## Assessing Readiness#

Once we know which opportunities are worth pursuing, the next question is whether the organisation is **ready to make them work**.

Readiness can mean different things for different opportunities. Does the required knowledge and data exist and can it be accessed? Can AI connect with the systems involved? Are the right people and processes in place? What permissions, governance and oversight will be needed?

For a business, helping support teams access product knowledge may look straightforward, but the relevant information could be spread across documentation, past tickets and internal systems, with different access permissions and varying levels of quality.

Understanding these gaps helps us see **what needs to be in place before an opportunity can move forward successfully**.

## Deciding How to Move Forward#

Once we understand the opportunity and what is required to pursue it, we can make a more informed decision about **what to do next**.

In some cases, the right answer may be to build a capability internally. In others, an existing product may already solve much of the problem. Sometimes the organisation may need to address gaps in its knowledge, systems or processes before moving ahead — and some opportunities may simply not be worth pursuing.

For a business, the decision might be to test an existing knowledge assistant for the support team rather than immediately building a custom solution, while first improving how its product knowledge is organised and accessed.

The outcome is a practical decision: **what to build, what to buy, what needs to wait, and what may not be worth pursuing at all.**

## What Comes Next#

By this point, the organisation has moved from a broad interest in AI to a clearer understanding of **where AI could create value, which opportunities matter most, what is required to pursue them, and how to move forward**.

The next step is to turn that direction into action — address the most important readiness gaps, test the assumptions that still need validating, and begin with the opportunities that make the most sense.

Getting ready for AI does not mean having everything figured out. It means **knowing where to begin and what needs to happen next**.

Figuring out where AI belongs — in your product or how your organisation works? **Let’s work through it together.**

### Organisational transformation with AI: *the Thoughtful Robots way*#

Organisational transformation through people, knowledge, systems and workflows, and the three connected areas of support: Advisory & Readiness, Workshops & Training, Installation & Maintenance.

### Learning to work *with* AI#

The practical skills, technical building blocks, role-specific understanding and judgement people need to use and shape AI in everyday work.