AI through the ‘business impact’ lens

With the recent advancements in AI, it is on top of everyone’s mind. AI is already drastically changing the work landscape, from delivery to experience. While a lot of techno-geek verbiage is out there, I wanted to structure my decades-long career in AI and put some structured thinking on what it means for businesses.

When I was doing my doctoral dissertation using AI/ML and Neural Networks back in the early to mid-nineties, few understood how impactful it would be in the future. The computational scalability was nonexistent, although the algorithms were very much in place. Now, with Cloud, Scalability, Reach, Volume, Velocity, and Variety of data across social media and the internet, both structured and unstructured data enable companies to rethink their businesses holistically.

Essentially, as Wiersema et al. (1995) had articulated in their seminal book “Discipline of Market Leaders,” business excellence centers around one or more of three dimensions — Product Leadership, Operational Excellence, and Customer Intimacy. Now that we have gained a lot of data and insights on Customer Intimacy, I would like to re-write it as ‘Customer Experience.’ My learning in Amazon came mainly from my experience as the North American Amazon Customer Experience Systems leader, where we leveraged Big Data to understand customer experience issues. The legacy that I left behind was to ‘take pictures of delivered packages in customer doors and send them emails with a snapshot,’ a massive program that reduced Logistics Costs by more than $100MM within just a year.

AI/ML solutions can be mapped to these three edges of excellence, as you can see in the diagram below:

As you can see in the image, Product Leadership is the forte of Apple and Pfizer — all else is secondary. Similarly, UPS, Walmart, and FedEx do not make ‘products’ — they deliver operational excellence. Finally, a great customer experience is what Amazon, Netflix, Google, Meta, and others aim to provide. Each of these areas has broad and deep applicability of AI.

Consider product leadership, for example. Generative AI can come up with millions of combinations of product features and ideas, resulting in huge efficiencies, along with ‘out-of-the-box’ ideas that have a clear impact on revenue growth and high efficiencies.

Operational Excellence has been using Machine Learning for decades. Predictive Analytics such as Sales Forecasting with Time Series Analysis, Multivariate Regression, and other tools are well known to businesses; they are being rebranded under AI, that’s all. Similarly, Optimization heuristics help supply chains fulfill demand with an optimized network at minimal cost to the company. Add to that Robotic Process Automation (RPA) that takes out repetitive, manual, process-driven busy work, returning valuable time to employees so that they can focus on creative thinking, influencing, negotiating, selling, and working with customers with empathy — things that AI cannot do well (yet).

Hyper-personalization based on your social media activity is something you must have experienced. You google something, and the next day, you see that ad on Instagram or Facebook. This is all based on AI-driven engines that amass vast volumes of data, resulting in revenue growth, subscriptions, awareness, consideration, and conversion. These digital AI marketing tools positively impact the ratio between Customer Lifetime Value (LTV) and Customer Acquisition Costs (CAC).

Please note that companies have typically worked within silos. AI will also help ‘connect the dots’ between silos. As such, leaders today must stay on top of all three functions.