How to Leverage AI in Your Business
It has been nearly six months since ChatGPT was released to the public, and while many have already seen the tremendous impact of artificial intelligence and machine learning tools on their business, others would rather treat it like a fad that will soon fade into irrelevance, like hoverboards, 3D televisions, or Google Glass.
Guess what? Artificial intelligence (AI) isn’t going anywhere — and if you think your business and industry are unique, and won’t be disrupted, you’re wrong. Does that mean you need to close up shop, and that everyone’s jobs are about to be stolen by technology? Of course not. But it does mean that even if you aren’t thinking about how to leverage the power of real-time AI technology in your business, your competitors are, and they’re going to gain a more and more competitive advantage until you catch up.
In this post, I wanted to provide a framework for how you can start thinking about using AI tools in your business — not to replace the value your company brings to customers and to the world, but to support and augment it, saving time and energy. (And, no, this post isn’t written by ChatGPT or OpenAI.)
The first and most fundamental thing to remember, before we even get to the steps, is that applying AI and machine learning, just like everything in the digital space, isn’t really a technology issue at its core. It’s a business issue, about efficiency and capabilities. Starting by asking what kind of technology you need is beginning with the wrong question. The place to start is by asking where the business value is, and what the best opportunities are in bringing the power and possibility of AI to bear. The critical follow-up question is ‘where is my business’ value at risk?’ from generative AI disruption or model bias.
Here is our framework for generating the greatest amount of value:
Step 1: Map the Opportunities
The first step is to create a market map of areas where you think your organization might benefit from AI solutions, trying to brainstorm as broadly as possible. Think about
- Revenue enhancement possibilities (processing and evaluating data to make better business decisions with pricing, for instance).
- Cost efficiency (workflow tasks that could use automation or use cases in which AI applications, like chatbots, could provide some help and support).
- The creation or development of new products or services.
Be sure to consider opportunities within the company — internal processes or capabilities — as well as customer and market facing possibilities. Don’t forget to consider your customer needs and marketing strategies along the way (social media, content creation, SEO). Innovation workshops or internal competitions can be useful in generating out-of-the-box ideas that may be worth considering.
Step 2: Size and Prioritize
Once you have your list of possible opportunities, sort them by the size of the potential impact to see where you might want to prioritize. Of course, high-quality impact isn’t the only driver here; you also need to look at how much effort each opportunity might take. Balancing effort and impact can help inform the priority list. Prioritization must also include assessing potential risks, but strategic use of artificial intelligence helps improve business processes and ultimately customer satisfaction.
Step 3: Solutioning and Capabilities
Here, you need to look at each opportunity through two different lenses.
- First, do you have the right people with the right capabilities to execute?
- If so, do they have the bandwidth, or will some current responsibilities need to be shifted? If not, can training on AI platforms help?
- Second, here is where you finally ask the technology question for the first time: do you have the tech you need to make this opportunity a reality?
- If not, do you have the ability to spec out the requirements and the necessary architecture, integrations, etc., or do you need to bring in a consultant to help?
It might be that at this stage, you want to focus on the low-hanging fruit — opportunities that you can quickly execute in-house with your current staff — before getting more ambitious.
Step 4: Detailed Planning and Approvals
It is short-sighted to think of this as a one-time exercise, or any particular project you choose to launch as a one-time initiative. AI is here to stay, and this is almost surely only the start for your business. If there are multiple opportunities that would draw on the same added infrastructure or staffing, it is okay to make those leaps.
This should be an ongoing process of building capability and transforming your organization. At the same time, of course, you need to create realistic and sensible plans when it comes to decision making for the budget, ROI, staffing, and external costs, and figure out the chain of command and who should sign off at each stage.
Step 5: Get Stuff Done
Agile methodologies are never more vital than in the case of constantly-changing technology, like what we’re seeing now with AI and machine learning algorithms. If you take too long in the planning process, the landscape may well have already changed by the time your project gets off the ground.
Think about increments of 2-3 months, not 2-3 years, and figure out how to get something built, tested, and deployed quickly, even if it’s not perfect. There will always be opportunities to iterate, and if you don’t make it happen now, the competition may get there first. Set long-term goals, but be sure there are short-term deliverables and chances to adjust all along the way.
At dPrism, AI is not the first technological breakthrough we’ve helped companies navigate, and it won’t be the last. We’ve had extensive experience, both as operators and advisors, finding our way through wave after wave of disruptive technology. We can help you better understand AI and its potential for your business, lead you through the process, and create significant impact that will yield results quickly. If you want to learn more about AI, contact us or check out another recent post about data-centric AI here.