Introduction
These days, most conversations revolve around AI, generating hype that rivals or exceeds the .com boom.
This hype has followed a typical arc:
- Massive excitement
- Deflated expectations
- A plateau at the bottom
- And now the beginning of a slow climb towards real productivity and use.
Understanding this curve is crucial - don't let either the hype or deflation affect your long-term outlook on AI. While most people's perspective on AI has been shaped by their experience with ChatGPT or similar platforms, AI encompasses far more than these tools.
The Big Question - What's Next?
In my conversations with CEOs, CTOs, government officials, and public agencies, everyone asks the same question: what's next?
While there's universal recognition that AI is significant and transformative, few know how to proceed. Even those considering AI projects face numerous unknowns, as expertise is scarce and state-of-the-art capabilities continue to rapidly evolve. We live in an interesting time where AI is both present and still emerging.
The best advice is to develop your organization's strategy for integrating AI-powered solutions, beginning with capability awareness.
Current State of AI
In the past year, AI technology, tools, and testing methodologies have evolved rapidly. This evolution has made enterprise AI integration more accessible, delivering more consistent and transparent results.
While risks like hallucinations or drift persist, new tools can detect and measure these occurrences. Many widely-used software products are integrating AI into their platforms, though often limited to chatbot-like experiences.
This integration will make companies more competitive and efficient but won't create disruption - it merely helps adopters keep pace with the status quo.
While this is one way your org will be introduced by AI, it will not make you any more competitive than other companies using the same tools.
Real disruption and progress will come from novel or niche AI applications solving specific problems. Rather than rushing into AI projects, focus on identifying unique opportunities that competitors haven't conceived.
You can only do that if you are aware of what AI can do - past the ChatGPT or canned solutions in existing platforms.
The Awareness Curve
For those monitoring AI developments but uncertain about next steps, building capability awareness is crucial.
The technology's rapid evolution means features that were experimental a year ago are now production-ready in enterprise settings.
Being merely a consumer of AI services puts you behind the curve.
Organizations should create cross-functional teams including IT, business, and operations representatives, as each brings different perspectives on AI's potential applications.
Attending top AI conferences often provides more valuable insights about state-of-the-art developments than months of reading. Understanding AI's potential benefits for your specific organization helps assess project scope and feasibility.
While true experts are rare, many have valuable perspectives to share. Increase your perspective through partnerships and collaboration within the field's rich community. Remember that everything in AI is evolving simultaneously: the technology itself, development tools and techniques, implementation methodologies, and debugging capabilities for LLM outputs.
Strategic Recommendations
- Create a team of subject matter experts who understand AI's capabilities and their unique business applications;
- Ensure cross-functional team composition for diverse perspectives;
- Engage with conferences, forums, and partners solving similar challenges;
- Focus on small, specific projects with rapid achievement potential;
- Even if new advances supersede your project, unique organizational benefits and gained internal knowledge provide long-term advantages.
Success lies not just in adopting the latest technology, but in strategically leveraging AI to solve unique challenges.
Stay informed and proactive—this is your opportunity to lead the way in innovation!