ChatGPT has become a topic of conversation in almost every business over the past 6 months. Since the AI chatbot launched in November 2022, the application has garnered more than 100 million monthly users. With numbers that impressive it’s difficult to ignore the impact, and potential, of generative AI in daily business operations.
With innovation comes trial and error, and the technology associated with generative AI is no different. Below, we discuss common snags in seen in the development and implementation of AI programs in business operations, causing them to over-promise and under-deliver over time resulting in lost investment.
1. Lack of Talent/technology Sourcing Strategy: As AI continues to grow in popularity, many leading developers are focusing on research rather than implementation. While this is great in theory, it may leave many folks with limited access to the technology. Finding a company that can take technology that is currently available and adapt it to address specific business needs may become a more reasonable option than working directly with AI inventors.
2. Concession to Technology Debt: Generative AI is ever evolving, so it is important to understand that technology work will be required to work out defects, add new features, and continued updates to infrastructure. To keep up with the latest developments in AI, constant innovation must be available, along with the funding necessary to do so.
3. Neglecting to Plan for the Future: As AI takes off in today’s business landscape, the excitement is real and many have jumped at the chance to be at the forefront of adoption. However, it’s highly important to plan ahead and look beyond the initial implementation to ensure that continued value is gained through the program.
4. Attempting to Solve Challenges Before Building a Platform: Building a solid AI platform is the best place to start. Once you have a program launched and in-use, review critical challenges one by one, prioritizing by impact to your operations. This will allow you to see the ‘big picture’ and invest energy and funding where it’s most impactful.
5. Remembering the Importance of User Experience: ChatGPT has become a household name not because it is brand new technology (the algorithm used to create it has been available since June 2020); AI has been capable of these types of interactions prior to it’s release. The design and ease of use are what catapulted the success of the platform. Ensuring a user-friendly interface is a necessity for success.
6. Failing to Restructure Management/operations to Fit a Digital Transformation: ensure that management is in place and ready to make the move to ‘human-in-the-loop’ operations. Focusing on restructuring roles to fit the service delivery of AI can help to ensure ROI is met.
Is your company an innovator, early adopter, or integrator when it comes in AI technology? While these labels aren’t mutually exclusive (many companies fall somewhere in between on this spectrum) it’s important to understand your level of AI maturity as you get set to launch a generative AI program. Understanding the above challenges and acknowledging realistic goals will help to set AI program up for future success.