With AI set to upend nearly every industry, one thing is clear for companies: the time to start thinking about how to strategically integrate AI into your business is now. If you don’t start exploring potential AI innovation, your competitors will beat you there. The problem is that, with a new and fast evolving technology, pretty much nothing else is clear.
How should you go about thinking through your organization’s AI strategy? While the answer to this question will be different in each industry and for each business, there is a step-by-step approach to breaking down this challenge that applies no matter your size or niche. This four-part framework will help organizations of all types get beyond AI hype to design solutions that actually advance business goals.
Step 1: Define the problem and identify opportunities
The first step in formulating an effective AI strategy is to clearly define the problem you are looking to solve. While AI has incredible potential, you won’t realize that potential if you just utilize AI for the sake of utilizing AI. Keeping up with the cool kids is not the basis for solid business strategy.
Instead, focus on identifying genuine business opportunities or challenges that AI may help you address.
The correct question to ask is: Why do we believe that there is a business opportunity or problem that can be solved through AI?
Starting with a well defined problem will align your AI initiative with your business goals and help you avoid wasting time and resources.
Step 2: Consider your timeline
Deciding when to implement an AI strategy is also critical. Yes, this is a fast moving space, but AI initiatives generally require substantial financial investments and resource commitments. Therefore, it's crucial to assess whether your organization is adequately prepared to support an AI initiative.
Waiting too long can cause you to fall behind. But rushing into implementing AI without proper preparation can lead to failed projects or suboptimal outcomes.
When is the right time? Factors to consider include available resources and potential market advantages. But keep in mind, given the current climate, for many organizations the answer to "When should we start?" is often "yesterday."
Step 3: Create a roadmap
Now you know where you’re heading and when to start. Next you will need a detailed plan that will hopefully get you to your desired destination. Before diving in, it's vital to conceptualize how your AI solution will be brought to market, as well as how you will measure its success once it's out in the world. Capture this information with a roadmap that lays out the steps needed for implementation, necessary support at each stage, and the key performance indicators (KPIs) you will use to evaluate the success of your AI initiative.
Thinking through this roadmap will help ensure your AI initiative not only delivers value, but is also scalable and sustainable.
This is the stage where you delve deeply into considering how the technology will work and how it will be integrated into your existing operations.
Step 4: The 3 pillars: data, algorithms, and infrastructure
Once you have your roadmap in place, the actual Implementation of any AI strategy rests on three key pillars: data, algorithms, and infrastructure. Let’s take them one by one:
- Data strategy: Data is the fuel for the AI engine. You will need to consider the types of data required, whether existing or new, to power your AI solution. Access to relevant and quality data is the key to unlock any benefits of AI. Start by understanding whether your organization possesses the necessary data in-house or if you will need to acquire additional data to fuel your solution effectively.
- Algorithm strategy: Algorithms are the heart of any AI application. These are the mechanisms for building models that lead to intelligence, and developing and deploying effective algorithms demand extensive expertise.Who will design, develop, and validate the AI models required for your project?
- Infrastructure strategy: Implementing AI systems also requires suitable infrastructure. This is the computational power required for processing data and information. As cloud computing capabilities have surged, the computing power companies can access has seen exponential growth. Determine where these systems will be hosted and how they will be scaled. Consider whether to deploy on your infrastructure or leverage third-party platforms. A well-structured infrastructure strategy ensures that your AI initiative will be able to not just launch but scale.
Crafting a successful AI strategy requires a holistic approach that includes problem definition, strategic timing, planning and benefit measurement, as well as careful considerations of data, algorithms, and infrastructure.
Keeping this framework in mind allows organizations to build their AI strategy on a sturdy foundation and avoid skipping essential steps that can lead to weaknesses of failures down the line. By aligning your AI initiative with your business goals and following a well-defined roadmap you help ensure that AI becomes a strategic asset that propels your organization into the future, rather than a distracting or wasteful effort to chase the latest trend.
This article was adapted from concepts taught in Stanford Online’s Building an AI-Enabled Organization course. Learn more about AI strategy and hear from leading experts in digital transformation by enrolling today.