Because data drives many—if not most—business decisions, CEOs need a thorough understanding of the impact and value big data brings to their organizations. More specifically, they need a better grasp on the value of one major application of big data: artificial intelligence (AI). A CEO risks falling short when it comes to envisioning an AI strategy. A McKinsey Global Institute survey of 3,000 executives found that 41 percent were unsure how AI could help their business. One way through that uncertainty is to understand the value of big data. Adopting a clear AI business strategy can be the first step.
Two Approaches to AI Strategy
Most businesses view AI either tactically or strategically, the tactical approach being more common. Those using AI tactically take a pragmatic approach to the technology. At this level, the main question becomes: How can we leverage this technology inside our existing business processes to either improve customer experience or reduce costs? This approach takes an app-based view of the technology, where an application is applied narrowly to a specific problem. For example, some businesses now deploy AI-based customer interaction apps. A customer calls for support and an automated voice asks the caller to describe their problem in a few words. Through machine learning, the app learns what certain word combinations mean, and it can either route customers to the appropriate departments or provide the customer with an automated answer.
On the other hand, the strategic view of AI takes what I call more of a “balance sheet” approach. Businesses with this approach view data as an asset, along the same lines as cash, accounts receivable, inventory, real property, and intangible property. Viewing big data as an asset changes an organization’s thinking. The questions become larger: How can we get the most value from our data? How do we protect it? How do we create new business from it? How do we use it to develop a more competitive product? How do we generate new revenue streams from it?
The Disruptive Power of the Strategic View
I recently bought a car. This car is much smarter than my old one, and it offers more value than simply being a mode of transportation. I can have satellite radio, a Wi-Fi hot spot, online traffic and weather, and navigation. These services add digital, data-driven value to my car. The manufacturer has taken the strategic view. They understand the customer’s point of view and have added things that make the customer’s life easier. These are services that customers are willing to pay for, which means new lines of business in a subscription model that continues to deliver revenue incrementally. As customers go through the buying experience and explore the use of these services, they become more immersed in the company. The customer relationship is reinforced by positive interactions with the brand, and that encourages customer loyalty. The manufacturer realizes that they no longer just make cars. The car has become yet another digital device, like a phone or computer. The car manufacturer enables the flow of data and, in turn, the data the user generates inside the vehicle will inform future updates and offers that the manufacturer can make. Cars provide an easy example because car makers have been at the forefront of AI and machine learning, but this AI strategy can be used by any business willing to view data as an asset.
The Costs of Ignoring AI
Both the tactical and strategic approaches to AI have their benefits, but I would argue that the strategic approach is the one to take to ensure the long-term health of your company. If you’re among the 41 percent of executives who are unsure about AI, or if your organization is using big data and AI tactically rather than strategically, you must take the initiative to make a change. Find a trusted advisor that can counsel you on the application of AI, the value of your data, and its implications for your business. Look for data teams that understand your vertical and have worked with others in your sector. This helps you leverage industry experience and removes the risks associated with innovation. Seek out solution engineers who can help you create a sustainable, scalable data infrastructure that provides the right value for what you need. There are many ways to implement a solution that is consumable, low-risk, and sustainable.
With AI, you can play offense or you can play defense. As with other tech innovations, the use of big data to feed AI is creating a competitive advantage. If you’re not using data in this way, you will fall behind. If your competitor is using data insights that drop costs below yours, your competitor wins. The same is true if your competitor uses data and AI to drive customer loyalty and immerse customers in positive experiences: those customers will never come your way. Not only are you competing on value—you’re competing for mindshare. Companies that don’t behave in a highly personalized, automated, real-time way are going to fall by the wayside.