AI has gone from hype to a crucial component of every company’s future data or analytics strategy. But organisations need the right foundations in place to start their AI journeys.

There remain robust discussions around the implications of artificial intelligence (AI) within the business. Forbes asks what ethical implications organisations should focus on when it comes to generative AI (GAI). The Financial Times looks at how AI is fundamentally changing the business of the MBA and its content. Stanford believes that the impact of AI on jobs and work comes down to a choice in the future. However, within this maelstrom of media and hype, there should be only one clear question – how can organisations extract value from data and AI?

Companies require support, infrastructure and advisory that leads them down the AI road in such a way that value is created at every touchpoint. For some, this may be the implementation of AI for predictive models that leverage their data to deliver insights that improve decision-making and planning. For others, this value rests within customer engagement. How can AI support the organisation as it connects with customers and delves deeper into their experiences, so loyalty and stickiness remain consistent? Then, of course, there’s how AI can benefit across chatbots, automation, business processes and digitalisation.

The value for the business emerges at the point where AI changes existing complexities and narratives into more powerful, results-driven experiences. And the technology can deliver a range of services across the value chain and business spectrum – from data management to data governance to maturing a digital transformation lifecycle, AI is invaluable to every business strategy. 

It has also gone well beyond the stage of asking ‘What if?’. Organisations should now be turning the page to ask, ‘What now?’. 

AI should be an inherent part of every company’s data or analytics strategies. It should also be deftly managed within a mature business ecosystem. An ecosystem that has prioritised investment into governance structures and maturity assessments that determine the success and progress of digital transformation and AI initiatives over time. These are essential foundations for any business wanting to work with data and AI more effectively – how else can any company evaluate whether or not AI is even coming close to meeting business expectations? It’s important that companies invest in these foundational layers with third-party advisory services designed to ensure AI, data, analytics, and insights are operating optimally.

The next consideration is the tools and technology used by the business to enhance and future-proof its AI investments. Organisations need platforms and capabilities that allow them to leverage both existing AI investments and planned AI innovation within an agile architecture that can evolve with their needs. If they want machine learning models or AI in production, then they need solutions that allow them to expand within these environments with ease. If they want to transform data from source to create value with advanced analytics by automating data into insights and intentional action, then they need the Insights-as-a-Service capabilities that AI can deliver.

There’s myriad AI solutions and technologies available on the market today, which makes it hard for companies to pinpoint the precise platforms that suit their needs. This is where advisory is critical. Everything from dashboards to data storytelling, advanced analytics to machine learning operations, anomaly detection, predictive analytics, and generative AI are realistically achievable within a strategic AI framework. It is also where the powerful BCX engine comes into play – offering comprehensive expertise, advisory, support and high-end AI solutions, BCX provides organisations with exactly what they need to answer the right AI question. The question that doesn’t ask “What if?” but rather looks ahead and answers the question of ‘What’s next?’. And the answer is BCX.