If it seems like you blinked and suddenly Artificial Intelligence (AI) was everywhere this year, you're not mistaken. Despite having been around for decades, the last few years (and months) have been especially formative for AI and the acceleration isn't going to stop anytime soon. We've started talking about the "half-life" of our thinking around AI because the technology is developing at such a rapid pace.
As a business leader, the constant evolution of AI is what makes this time particularly difficult. How can organizations plan and execute on a technology that’s changing rapidly and many leaders don't fully understand? Fortunately, there are some foundational aspects and considerations for AI that can help with this. A solid understanding of these considerations can help business leaders create a plan for integrating AI into their company's future with more confidence.
A Brief History of AI
While most people are more interested in the progress made in AI technology over the past six months, understanding its history will provide a little bit of context. In the 1950s, AI was referred to as a deterministic technology (basically a big series of if-thens). Fast-forward to today and AI is now considered more as a probabilistic model that uses large sets of data to statistically predict the next node in a series based on probability. More recently, things with AI have begun to speed up. In 2016, Google declared themselves an "AI-first company," literally inventing the 'T' (or Transformer technology) in “GPT”, that led to big advances. Fast-forward to the beginning of 2023, when OpenAI takes its GPT technology and wraps it in a chatbot and creates chatGPT. That gets us to the present – well, almost.
In the subsequent months, Microsoft began integrating OpenAI's GPT technology into its search and office suite of products, with other large tech companies following suit. Google released its own generative chat technology called Bard and subsequently rolled out additional AI offerings including PaLM 2. Amazon also released Bedrock on top of its existing suite of AI tools that includes SageMaker and others. For many companies, this means that their existing technical architecture may have an extension of AI services that is currently (or will soon be) available for implementation.
Industry Applications of AI
Many companies are actively assessing the potential of AI for their business, and those applications could look different depending on the industry. For banking and insurance, financial analysis and fraud detection might be good places to start. For retailers, demand forecasting or customer personalization may be places to explore. Companies looking to increase the capacity of their development teams will look at code generation tools and AI-powered automated testing. Distribution and logistics companies are looking at route optimization and dynamic pricing to realize efficiencies in their operations. Historically, being an early adopter of new technology might not have been necessary for companies in most industries, but falling behind to competitors with AI will be harder to make up. This technology presents businesses with new opportunities and significant advantages, even as pilots in the near term.
Considerations Around AI
There are several important things to consider as businesses explore applications of AI across their business. As always, the quality and organization of data, coupled with the maturity of internal service architecture, can be technical impediments to realizing the full value of AI. Next, robust oversight and governance of AI initiatives are critical to managing the risks that can be associated with this technology. Finally, consider how you will properly train your workforce to effectively integrate AI into all business functions, or if it’s best to find a partner to help with your AI implementations and transitions.
Cautions for AI
A healthy understanding of the risks associated with AI will help companies implement the appropriate governance and operational controls as they introduce these technologies. There are security and privacy implications to how companies manage their data and use it for applications of AI.
Additionally, there are compliance considerations that AI implementations may or may not be equipped to observe. A myriad of ethical considerations exist around bias, explainability, and intellectual property rights. These risks should not dissuade organizations from exploring the uses of AI, but responsible leadership will require this kind of governance be in place as solutions are developed and deployed.
The Next Phase of Innovation
AI is about to radically transform many companies from the inside out over the next several years. But rather than being overwhelmed by the technology or fearful of it, responsible companies will begin to educate their organizations about the potential of AI and create spaces to explore its use. As a starting point, consider small pilot initiatives with clear guardrails around their use. Work on iterative initiatives that can be responsive and adaptable to the rapid roll out of enhancements and features, which will be the constant for the foreseeable future. AI is launching us into an exciting phase of innovation, providing companies with new ways to succeed and serve their customers. Let's get to work.