Amid the growth of the Artificial Intelligence (AI) and big data market, business leaders are starting to realize that AI – like any other business function – requires structured strategy, planning, training, and execution to successfully implement.
Many companies working on digital transformation have amassed huge data archives but lack the ability to extract the information they need to unlock new synergies and growth paths. This bottleneck is visible in most companies I meet. The transition from data collection to fully formed, AI-driven growth strategy is a multi-step process that can appear overwhelming to those without clear guidance.
If this describes your own situation, read on. Below are three key areas that CIOs can focus on right now that can make a lasting business impact through the implementation of AI.
[ Check out our primer on 10 key artificial intelligence terms for IT and business leaders: Cheat sheet: AI glossary. ]
1. Leveraging AI to optimize core business operations
While most companies profess to be “digital,” the reality is that many boardrooms still view digital strategy as a bolted-on process that supports existing operations – the renewal of a company’s administrative support layer. Many CIOs face a constant battle to underline the impact true digital transformation can make when properly implemented and supported by AI.
[ Read also: Digital transformation: New data shows speed gains – and culture worries. ]
Even so, most companies have built a data capture layer on top of their operations. This is the opportunity CIOs need to get the ball rolling. The benefits real-time data delivers for predictive maintenance and manufacturing pipelines are well documented, yet the true opportunity doesn’t just lie in highlighting incremental efficiency improvements. AI allows CIOs to explore their data and find entirely new ways to deploy existing assets that have the potential to significantly impact the company’s bottom line.
By initially focusing on low-hanging fruit and easy wins that deliver results, I have seen CIOs win over hearts and minds in the boardroom. The momentum provided by these wins makes it easier to persuade leadership to capitalize on larger transformations, including potential pivot opportunities discovered by AI.
[ Want best practices for AI workloads? Get the eBook: Top considerations for building a production-ready AI/ML environment. ]
2. An AI-first approach to creating entirely new business models
2020 has shown that the ability to think and act swiftly can mean the difference between survival and bankruptcy for organizations of all sizes. Sedate planning and cost/benefit forecasting based on historical data has less value in volatile, novel, and unpredictable market conditions.
In response, many companies have adopted an AI-first approach to setting company strategy. Their data strategy centers on building a deep, real-time understanding of their customers so they can quickly adapt when actions, habits, and preferences change.
A knock-on benefit of this deep understanding is the potential to create an ecosystem of offerings to cater to more customer needs. Tesla, for instance, has tightly focused on its customer’s buying, usage, and maintenance patterns. As a result, it has launched a successful AI-powered insurance offering that outperforms competitive services from rivals with a more superficial view of their customers.
3. Building data-driven services to pair with current offerings
Something of a middle ground between the first two options, this might represent a steppingstone for company leadership teams that want to do more than simple process optimization but might not yet be ready to make the jump into an entirely new industry. Equally, a truly data-driven service offering may be the competitive edge that pushes your company to the top of the market.
In a highly vertically integrated business, CIOs can build reporting tools and service platforms that can be licensed and sold to other operators in the same space. The usage of these assets can also provide new valuable data streams to increase learnings and improvements. Equally, in companies with more horizontal integration, AI-powered tools built in partnership with other players in the same value chain can deliver value for all who take part.
While this course of action creates a new source of revenue for your company, the offering still serves the same industry and the learning curve for market entry is less steep. Apple is a good example of a company with comprehensive vertical integration that continually builds new data-driven service offerings such as the upcoming Apple Fitness+ service powered by Apple Watch customer data.
Get on board
Almost all modern companies are dipping their toes into the AI waters at some level, yet there is still some hesitance in taking the full plunge. As a CIO, your task, while not easy in the beginning, is clear: to clearly demonstrate to your board in a step-by-step way (backed by solid data and financial figures) that data and AI are central to your company’s long-term prospects. Gone are the days where company lifecycles take a century to unfold. If the world changes faster than you do, you will be left behind.
However, CIOs have an opportunity to get real work done by helping other business leaders understand that the old way of thinking – with different department heads protecting their turf – is less effective than a fully connected, synergistic business with all parts working in harmony and moving forward with purpose. We know AI and data are the keys to unlocking this potential. Now is the time to get others on board.
[ Culture change is the hardest part of digital transformation. Get the digital transformation eBook: Teaching an elephant to dance. ]
