As ChatGPT has demonstrated, AI tools are changing the way companies, large and small, are thinking about the future. In just a few short months, everyone is trying to figure out how to capitalize on generative artificial intelligence (AI) models like Chat GPT. So how will generative AI change business?
While there have been significant AI initiatives for more than a decade, many were focused on deep learning through unstructured data sets. Not exactly user-friendly to regular people. The release late last year of ChatGPT from OpenAI changed all of that. It was simple to use, easy to see the results, and demonstrated to many people how AI could handle tasks reserved for humans. Over a million people used the product in the first five days after its release.
According to a recent article from McKinsey, “computers can now arguably exhibit creativity. They can produce original content in response to queries, drawing from data they’ve ingested and interactions with users. They can develop blogs, sketch package designs, write computer code, or even theorize on the reason for a production error.”
Suppose you categorize economic activity into McKinsey’s three areas in the early 2000s: production, transactions, and interactions. It’s easy to see that interactions have been the least impacted by technology until now. Generative AI has shown the ability to imitate human behavior, though it will still need human input and support. It will be most effective when used with humans, allowing them to work more efficiently and effectively.
We’re just scratching the surface with this technology, but adoption is happening quickly. As the article notes:
- Marketing and sales—crafting personalized marketing, social media, and technical sales content (including text, images, and video); creating assistants aligned to specific businesses, such as retail
- Operations—generating task lists for efficient execution of a given activity
- IT/engineering—writing, documenting, and reviewing code
- Risk and legal—answering complex questions, pulling from vast amounts of legal documentation, and drafting and reviewing annual reports
- R&D—accelerating drug discovery through a better understanding of diseases and discovery of chemical structures
Generative AI is exciting, but businesses must approach it with thoughtful caution. It is still in its infancy, and there will be bugs and learnings that we haven’t seen yet, not to mention the ethical issues that will surface. It’s important to remember that humans develop generative AI and create the content it uses to generate its output. This is to say that, just like humans, it can be wrong. The article calls these hallucinations “meaning it confidently generates entirely inaccurate information in response to a user question and has no built-in mechanism to signal this to the user or challenge the result.”
As businesses think about how to use generative AI, it’s essential to realize that company culture will not be reflected in the technology. One day companies may be able to “teach” it their values, but today, it is most likely out of reach.
Those who want to adopt generative AI should consider where it will be most beneficial to their business, when and where they can implement it, and how they’ll keep an eye on the constant iterations of the technology. The article suggests assembling a cross-functional team including legal, data scientists, and business leaders, and questions that should be addressed:
- Where might the technology aid or disrupt our industry and our business’s value chain?
- What are our policies and posture? For example, are we watchfully waiting to see how the technology evolves, investing in pilots, or looking to build a new business? Should the posture vary across areas of the company?
- Given the limitations of the models, what are our criteria for selecting use cases to target?
- How do we pursue building an effective ecosystem of partners, communities, and platforms?
- What legal and community standards should these models adhere to so we can maintain trust with our stakeholders?
Generative AI will undoubtedly change businesses, but the innovations it will drive remain to be seen.
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