By Steve Morland, CTO, Leighton
Artificial intelligence continues to dominate conversations as generative AI has become part of the everyday experience of most internet users, and machine learning is adopted in more and more industries.
There’s a lot of discourse already out there about AI’s potential to transform our work and home lives, but thanks to the ChatGPT boom, it’s becoming something most of us can’t ignore. For business leaders, if you’re not already using it, you might be feeling the pressure to just “get some AI”. But like any technology, adopting it into your business should be considered strategically and deliberately.
In this article, we’ll explore the steps you can take to get started with AI, starting with the first crucial question: what problem you are trying to solve?
1. Put your business needs first
Successful AI adoption relies heavily on aligning initiatives with immediate business needs and goals. Rather than thinking about how you can adopt AI into your business, think about a problem you need to solve. Whether it’s enhancing customer engagement, streamlining operations, or optimising a business-critical process, AI solutions must directly contribute to business outcomes and clear success measures.
2. Start small
Now you’ve identified a problem, it’s a good idea to start small. Focus on manageable, isolated implementations which will allow your business to pilot AI technologies without disrupting existing systems or overburdening resources. Use it as a bit of a learning phase, enabling your teams to evaluate AI’s impact on specific processes and refine strategies iteratively. You could tie this in with a proof-of-concept approach, where you trial different tools and technologies (or indeed custom software) to prove viability. Starting small means you can mitigate risks, optimise outcomes, and build confidence in AI’s capabilities before scaling across the business.
3. Get your data ready
Before integrating AI into your business operations, it’s important to ensure your data is prepared. AI and machine learning algorithms perform best with high-quality, well-organised data, and the outcomes are only as good as the data that goes in. To ensure your data is ready, you might audit your data or carry out some data cleansing to eliminate inconsistencies, biases, and inaccuracies that could compromise AIdriven insights.
If you’re in a heavily regulated industry or you have to comply with laws concerning data (hello GDPR) you need to establish data governance practices to protect sensitive data and ensure ongoing data integrity. Preparing your data accordingly will enhance the effectiveness of AI applications, enabling your businesses to gain accurate insights and make informed decisions.
4. Prepare your team
If you’re considering AI adoption, it’s important to adequately prepare not just your technical teams but also teams spanning all areas of the business. Whether it be change management initiatives or technical training, by investing in education and upskilling, businesses can not only equip their teams to leverage AI effectively but can ensure everyone understands AI’s potential and can contribute effectively to its implementation and ultimate success.
By prioritising strategic alignment, iterative implementation, data integrity, and team readiness, you’ll have everything you need to navigate the complexities of AI adoption with confidence.
leighton.com