Mar 22, 2024
Apr 3, 2024

The Secret to AI Success

Learn to build a successful AI strategy with a 'start small, scale fast' approach, ensuring quick wins and long-term value in your AI journey.

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Are you looking to build out your AI strategy and AI roadmap? Stop and read this before you go any further!

We are going to share how we recommend approaching AI within your organisation to deliver results.

We’ve seen many organisations spend a ton of time mapping out their AI strategy by hunting down use cases, setting up governance rules, wrangling their data, and splurging on tech. However, this process just ends making you feel like you are not making any progress, tying you in knots, and even worse it can lead to your work being questioned before it has even really started.

Instead, we recommend starting small and scaling fast and in this blog we are going to help you apply this approach in your organisation to ensure that your AI implementation delivers real value.

Intrigued to find out more? Then read on as we cover:

  • Why we advocate a start small and scale fast approach
  • How to find your first AI project
  • How to build out your AI strategy and roadmap based on this approach

A start small and scale fast approach

So what exactly do we mean?

Unless you already have great data, technology, a big fancy AI team, and very supportive leadership you are going to have to prove that AI technology works quickly and drives value to get buy-in. It’s not that you are not going to think big, but you need a stepping stone to the big transformation that AI will bring. All too often we have seen projects fall down by starting big and failing to deliver value quickly enough.

Remember, organisations don’t want to be waiting for years to see any tangible progress, they want to see results fast, they want to see that their investment is paying off and you are on the right track. This will then enable you to work on the long-term priorities that will deliver even more value to the organisation.

How to find your first AI project

So, how do you go about finding that first AI project that is going to deliver big benefits, quickly, enabling you to start small, get buy-in and scale quickly.

Within your organisation you are looking for the quick wins, these are often found in the tasks that are very manual for employees or customers, using what we call unstructured data, so voice, text, and video. These are the ones that are ripe for your first application of AI as they:

  • They have the potential to save a huge amount of time, effort, and money
  • They don’t usually require you to spend ages sorting out your data
  • They usually don’t require drastic changes in your technology stack
  • They don’t take a huge degree of training and upskilling

Focusing on these types of projects will get you the buy into think bigger and help smooth the way for using AI across your organisation.

Examples of the types of manual process that we are talking about are:

  1. Processing contracts, applications, or claims - JP Morgan Chase were able to use AI to analyse financial contract analysis in seconds what would have taken lawyers 360,000 hours to complete
  2. Manual validation of interactions for regulatory compliance – manually checking audio recordings for compliance can be time consuming and prone to human error. Utilising AI can reduce the need of having a large team to validate that your customer interactions are compliant and up to scratch
  3. Reducing the contact centre load – the fintech, Klarna’s, introduced a new AI assistant to reduce the load on their contact centre. In it’s first month it handled two-thirds of customer service enquiries, reduced the time to customer resolution, and the amount of customers calling back. All this while doing the work of 700 full time agents

As you can see, these are such great first use cases, as they have a direct return on investment, can be easily quantified, and the benefits are easy to understand by everyone.

Augmentation is another avenue for embedding AI, but in a lot of instances the benefits are harder to quantify, and they aren’t as transformational.

Building your AI Strategy and AI Roadmap

Starting to build an AI strategy may seem daunting, especially for those not from a deep technical background. However, while your AI strategy will be unique to your organisation and its goals and challenges, there are core elements that every organisation needs to cover to break down the challenge of adopting AI and sell the vision to senior leadership and your peers.

The first element is that every organisation must mature across five critical pillars that supports AI adoption. They are:

  1. People & Talent – making sure you have the right people with the right skills to make the magic happen.
  2. Technology & Tools – ensuring that you have the infrastructure, compute, and tools available to crunch the data and support solutions
  3. Governance – Keep things in check with rules and oversight to reduce risk and ensure adherence to regulation
  4. Data – it’s all about the availability of quality data at scale to support AI models
  5. Processes – Set up the right systems and workflows to ensure AI gets used the right way

Next, lets talk strategy! Your AI strategy and roadmap should follow a logical flow, covering a few basics:

  1. Why AI: Get focused on why your organization needs AI and how it fits into the big picture or vision
  2. How AI Helps: outline the potential benefits and problems that it can solve that align back to the vision
  3. Getting Started: introduce the five pillars we talked about earlier and how the organisation needs to mature in these key areas
  4. Outline the plan: lay out your plan of attack
    - Your short vs. long term plan
    - Introduce your quick win projects to start small and scale fast
    - Raise the risks and outline how you will address them
    -Pinpoint who needs to be involved and the roles and responsibilities

With these steps and knowledge you can craft a killer AI strategy that delivers results quickly.

Every organisation needs a plan for embracing AI, but putting together an AI strategy shouldn’t be a painstaking process that takes months and put you on the back foot.

By following the framework and guidance in this blog, and focusing on quick wins to deliver results quickly, you can set yourself up for success.