Artificial General Intelligence (AGI) and Agentic AI

First off, what do I mean by Artificial General Intelligence (AGI)? Think of AGI as machines or systems that can handle intellectual tasks the way humans can and actually learn from their actions. Agentic AI takes that a step further by turning this intelligence into AI "agents" that can collaborate with other agents and make decisions on their own.

Personally, I’m ready for an AI assistant to follow me around and make all the decisions I don’t want to. Imagine telling it, “Make me lunch,” and not needing to spell out every detail because it just knows what I like. Of course, this could go hilariously (or terrifyingly) wrong. What if it learns my allergies and decides to sabotage me if I “mistreat” it? Can we program that kind of pettiness out? Sure. Could it override that with its own learning? Yeah… probably.

But jokes aside, Agentic AI is already capable of making a huge impact, and some experts think we could see fully developed AGI within a decade.

What AGI Will Be Able to Do:

• Integrate and analyze multiple data streams—like manufacturing, supply chain, global weather, and economic forecasts—all at once.

• Invent solutions for problems that would take top-tier consultants millions of dollars and 18 months to solve. :P

• Automate basic tasks like data analysis, freeing people up for more collaborative, relationship-driven work.

Take, for example, a patent filed by Brian McKarson and his team for “Generative AI and Agentic AI Systems and Methods for Product Data Analytics and Optimization.” This system uses machine learning, large language models (LLMs), and intelligent agents to predict things like product sales, inventory, and pricing. It processes real-time data—think sensor feeds, economic reports, and images and constantly learns and improves. The result? It spots trends, generates actionable insights, and makes lightning-fast decisions, like executing trades or fine-tuning strategies, far faster than any human team could. This patent is a big leap toward AGI, particularly in areas like economic forecasting and product analytics.

What Should Companies Do to Prepare?

1. Get Your Data House in Order - Before diving into AI and AGI, companies need to nail down the inputs. I’ve lost track of how many leaders I’ve talked to who want “AI” but haven’t even set up basic data structures, metadata, or processes. Start there.

2. Define Your Ethics and Guidelines - Governance, transparency, and ethical AI will separate the winners from everyone else. But don’t just play it safe—businesses also need to push boundaries and experiment to stay ahead. The key is balancing responsibility with bold innovation.

3. Communicate Your Strategy - AI is already changing jobs, but it’s also enhancing your workforce. Be upfront with employees about how AI fits into your strategy, and ask for their input on where it can create the biggest wins.

At the end of the day, I’m beyond excited for AGI. I can’t predict when I’ll finally get my personal assistant robot, but one thing’s for sure: I will not be giving it the list of foods I’m allergic to. Just in case.

References:

"Researchers Submit Patent Application, 'Generative Ai And Agentic Ai Systems And Methods For Product Data Analytics And Optimization', for Approval (USPTO 20240256598)." Information Technology Newsweekly, 20 Aug. 2024, p. 5842. Gale Business: Insights, link.gale.com/apps/doc/A805219131/GBIB?u=umuser&sid=bookmark-GBIB&xid=8cfe7e48. Accessed 17 Dec. 2024.

Laney, D. (2024, December 16). Beyond AI: Preparing for artificial superintelligence. Forbes. Retrieved from https://www.forbes.com/sites/douglaslaney/2024/12/17/beyond-ai-preparing-for-artificial-superintelligence/