Jose Tamez is Managing General Partner at Austin-Michael, an executive search firm in the retail, wholesale and branded channels based in Golden, Colo.
Artificial intelligence, AI, seems to have the same forewarning as “The British are coming!” – Paul Revere’s famous cry on that April night in 1775. But even Paul himself knew that the British were already here. So has been the case with AI.
Its origins go back to 1950 when Alan Turing published his work “Computer Machinery and Intelligence”. It eventually became The Turing Test, in what was used to measure computer intelligence. In 1952 computer scientist Artur Samuel developed a program to play checkers, which was the first to ever learn the game independently. John McCarthy, Princeton Ph.D. in Mathematics, held a workshop in 1955 at Dartmouth on “artificial intelligence” which is the first use of the phrase.
Let’s first distinguish between AI and GenAI (Generative AI or Advanced AI). AI involves using data analysis to identify patterns, make predictions, interpretations, and perform specific tasks. It operates on predefined rules, making its decision-making process more transparent and interpretable. GenAI creates original data based on human input and data analysis, much like a creative content assistant. It can create writing, music composition, new media, image generation, etc., plus relies on deep learning for its ability to create new content. As an example, you can plug in an idea and it will expand on that idea, fill in gaps plus provide alternatives. So, to be clear, GenAI needs a human command — more on this in a bit.
As most of us know, it’s GenAI that is being labeled as a replacement for many in the workforce. To be sure, its proliferation has varied implications across labor markets. Specifically, those in the highly skilled, white-collar work and roles defined in a knowledge economy — rich in data-driven tasks and structured processes. At minimum a future transformation across nearly all types of these roles will take place, while blue collar work will remain relatively unaffected.
The adoption of GenAI is based purely on augmenting workers’ productivity and effectiveness to capitalize on new technologies and new unit economics. Interestingly, the increase in output because of GenAI doesn’t assure a reciprocal growth in demand for goods and services. Moreover, the challenges with GenAI are as follows: Not especially original — may produce imitated content, limited critical thinking, low emotional intelligence, limited factual accuracy, data privacy, and security concerns.
Further, GenAI has its early challenges related to delaying its adoption. From investments in the millions to assembling teams, breaking down silos, and setting up methodology, it’s clearly not on the verge of taking over all industries next week. In fact, most companies claiming they are currently doing AI or “Powered by AI” are doing traditional AI as opposed to fully fledged GenAI or Advanced AI at scale. Issues on security, privacy, licensing, and proprietary have led to many companies, including in retail, to ban a form of GenAI – ChatGPT from being used company-wide.
Those propagating companies’ need to get on board fast seem to be the ones who are profiting from its growth and what many analysts claim to be its overvaluation — overestimated in the short term, and possibly underestimated in the long. Many that are bullish on AI still want to see true results rather than hype. They also categorize AI as being part of the next tech cycle as opposed to a panacea.
Again, AI needs an input of a command, most likely human. In the near term and in the main, AI in and of itself is not going to take one’s job. Someone who understands it migh,t though. Think of it the same way as in the past when technology didn’t take your job, but someone who was tech savvy did.
Companies are going to try and fully leverage AI but most will not have the budget to build the infrastructure, so they’ll likely rent the infrastructure from other companies. However, AI is the next hard skill in our evolving economy. Education through post graduate programs across the country is now available, but at a minimum acquiring working knowledge is a must if your job has exposure here.
Finally, as GenAI / Advanced AI disrupts conventional roles, there will be a premium on human skills such as critical thinking, empathy, and adaptability. Companies can achieve optimal outcomes when they marry the capabilities of GenAI and human intelligence. The blending of art and science still produces our greatest achievements.
