The current hype around generative artificial intelligence is such that vendors are flooding the market with big promises, sometimes too good to be true. If we believe some, only a few would be needed encourage so all your problems are solved.
Contribution of Alan Trefler, President of the Pega Management Board
While the power of generative artificial intelligence is real, there is no one-size-fits-all solution to all business challenges. And generative artificial intelligence is not the only artificial intelligence on the market. Other types of artificial intelligence, each with their own flaws and qualities, can fulfill different business goals.
Unfortunately, too many vendors are taking advantage of the current craze to present their generative AI tools as a “Swiss Army Knife” that can solve ALL of your problems. In addition to false promises and confusion, many of these generative AI products lack the control, management, and scalability capabilities that large enterprises need.
To avoid making the wrong decisions, it’s important to learn more about the different types of AI available for each type of problem. Artificial intelligence can be divided into two categories.
“AI right brain” for creativity
The first category of artificial intelligence, “right brain”, refers to creative tasks. Generative artificial intelligence falls into this category.
It developed at breakneck speed. It is most often used to create content: articles, images, audio files, videos or even applications. (I may have even used a little generative AI to write this article…but that’s between us.) It also excels at content summarization (like meeting minutes) and multilingual translation. It’s even capable of coding, although that’s not necessarily a good idea, but that’s a topic for a future article.
“Left brain AI” for rational thinking
While all eyes are on “right-brain” generative artificial intelligence, we’re forgetting an important point: it doesn’t help make decisions based on logic and analysis. For this you need another category of artificial intelligence, that of “left brain”.
It is essential to optimize business decisions. She is able to assess situations, predict outcomes and take decisive action, either in cooperation with people or independently in less critical cases. It can take different names: predictive analytics, process mining, logical reasoning, real-time decision making, etc.
This AI will be able to recommend a product to a customer, approve a bank loan, assign a request to the right agent, or even resolve customer service issues. Some companies rely on its analytical capabilities to automate millions of business decisions every day, making it a central part of their day-to-day operations.
Use both hemispheres of the brain
If you use creative (right brain) intelligence for tasks better suited to analytical (left brain) intelligence, or vice versa, you could be disappointed, if not worse. More and more organizations are making this serious mistake and risk having to face criticism.
But there is a balance to be struck: to harness the full power of artificial intelligence, you need to use both the left side of your brain, to make analytical decisions, and the right side of your brain, to create content. This association is key to achieving all the promises of an autonomous enterprise.
For example, left brain AI will be able to analyze customer engagement data and provide insights in real time on their journey with your brand, while right brain AI will be able to use them insights create interesting content or offers adapted to the needs of that customer, which significantly strengthens the relationship with the customer. This collaborative approach to artificial intelligence helps optimize the customer experience and the company’s growth potential.
Towards a speculative bubble around artificial intelligence?
As excitement around AI grows, organizations that have invested in the wrong kind of AI may find themselves starting over, and some of their suppliers may disappear. There will be great disappointment when the bubble bursts.
But the story will not end there. We have barely scratched the surface of the potential of artificial intelligence, whether creative or analytical. To avoid falling behind, organizations must continue to implement and test all types of AI to find the formula that works for them.
But they must remain cautious and scrutinize the various promises of these AIs. This is the best way to avoid the consequences of the bubble and be ready for the era of autonomous business.
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