Is AI Plateauing?  Does it Matter?

Artificial Intelligence (AI) has transformed industries and workflows, but is it hitting a plateau? As the initial excitement over AI breakthroughs settles, two potential signs of stagnation have emerged:

1. The Quieting of Enthusiasm
   The buzz that once accompanied AI innovations has noticeably mellowed. Groundbreaking milestones like self-driving cars or real-time translations stirred public imagination, but subsequent updates, while incremental, have lacked the same “wow” factor.
   
   
2. Diminishing Impact of Recent LLM Updates
   Recent updates to large language models (LLMs) have made improvements, but they’re often perceived as refinements rather than revolutions. For ChatGPT users, how much better do you view 4o vs. 4 vs. 3? The incremental benefit appears smaller with each new release, leading to skepticism about how much further these tools can go.

But this doesn’t mean growth has stopped, far from it! For organizations leveraging AI, this is the perfect moment to refine and evolve strategies. Here are three ways to continue driving value from AI:

1. Hone Your Prompting Skills

Prompt engineering is the key to unlocking the full potential of AI. Teams should experiment with structuring questions and commands to yield better results. For example, specifying a desired outcome or style can lead to more actionable outputs. Regularly test and document what works best in your context to build a shared knowledge base.

Take time to watch Youtube tutorials, etc. To quote a team member “I thought I was an 8 or 9 out of 10 when it comes to prompt engineering. When I saw what these specialists can do, I realized I was probably at a 3.”

2. Pursue Strategic Projects Beyond the Basics

The low-hanging fruit (simple automations and one-off reports) may already be addressed. The next step is identifying and prioritizing more complex, high-impact projects. Take the time to reassess AI’s strengths and which improvement projects best align to those strengths. Do still take the time to assess the ROI of implementing AI, the goal is efficiency, not just to implement AI.

3. Encourage Cross-Team Collaboration

AI is a team sport. Create forums for team members to share their approaches, successes, and lessons learned. Bring in an employee from a different functional area to gain a fresh perspective. AI may solve a specific need, but its applications can be universal. Regularly revisiting how tools are being used across departments can spark ideas and foster innovation.

Moving Forward with AI

Instead of focusing on the potential plateau, view this phase as an opportunity to deepen your AI expertise and extract more value. By refining usage, tackling more strategic initiatives, and fostering collaborative learning, your team can stay ahead in this evolving landscape.

AI may not always dazzle with new tricks, but its potential to transform your organization is far from exhausted.