Climbing the right wall: Unlocking business value through AI

By Bidhan Roy, VP – Analytics, Research and Data, Fidelity Investments India

Artificial intelligence (AI) is a powerful tool in project management, when used as a means of enhancing and complementing human creativity and innovation. In this context, I often think of the example of a ladder against a wall. The ladder signifies AI, and the wall stands for the overarching strategic objectives that the project team is seeking to accomplish. The wall, looming large before the team, can seem almost impossible to scale at first, until the ladder is spotted. The ladder, with its multiple rungs, becomes an effective tool to achieve successful outcomes. It’s important, however, to align the ladder correctly with the right wall – the technology with the business strategy.

Too often, teams become overly focused on the technology itself and complex models without first ensuring it is in sync with the broader business strategy. This misalignment leads to a poor use of resources and missed opportunities for value creation. 

Teams could overcome this, however, by clearly defining the business objectives and aligning the AI suitably to these, to successfully achieve innovation through AI. Essentially, this means shifting an AI builder’s focus from merely developing technical components to ensuring the components that are developed come together to align with the overall strategy. 

Business strategy and technical expertise go hand in hand – the ladder needs the strength of the wall to achieve the desired results. This approach will be instrumental to realising the real value of AI.

Here are some of the ways in which we can work to ensure the best outcomes are achieved through a strategic business alignment of AI efforts:

1. Clear objectives: In many projects involving the use of AI, the process of developing the AI solution can take on a life of its own and cloud the strategic objectives behind the problem. Without clear objectives, it’s easy to apply AI in areas that do not lead to a meaningful impact. Hence, it is best to start any project by clearly stating the objectives, so that each member of the team is on the same page and aligned to the same goals.
2. Need for quality data: Quality data underpins the success of an AI project. Sometimes, AI models are ineffective or biased owing to data silos, poor data quality, and inadequate data governance. This is similar to having a ladder that seems nice and strong when you look at it, but when you set it down and try to climb up, you find some of the rungs are missing. It is essential to identify the right data that are best suited to achieving the project’s strategic objectives.
3. Knowledge and expertise: The implementation of AI requires a mix of domain knowledge, technical expertise, and strategic insight. Adequate attention needs to be given to ensuring team members are trained and equipped with the skills and expertise needed to address the project objectives. 
4. Aligning efforts to outcomes: Often, a disproportionate amount of effort goes into developing complex and technically impressive AI models that don’t lead to significant results. Good planning both at the start and throughout the process can ensure this is done right.

To fully explore AI’s potential, it is essential for teams to shift their approach from merely building the steps of the ladder (building AI solutions) to aligning the ladder with the right wall (the strategic objectives). AI thus becomes a more effective tool in adding value to the business.