Digital Economy Dispatch #217 -- My AI Strategy for 2025: Less Noise, More Signal

As we begin 2025, it’s a good time to turn the page and start a new leaf. Having seen out the old, we celebrate the new and reflect on how to face the world. What will the new year hold, and how will we approach the opportunities and challenges that await? These are questions we all ask ourselves at this time of year.

Seen from my personal perspective, in my journey to understand the role of AI in driving digital transformation, it has provided an opportunity to reflect on where to place a priority for 2025. Over recent months, AI technology has become ever more deeply embedded in our digital world, with AI-based content generation tools now accessible to everyone with an internet connection. While this democratization of AI brings exciting possibilities, it has also created significant challenges that will be at the forefront in 2025.

The digital landscape is becoming overwhelmed with AI-generated content, as marketing teams and content creators leverage these powerful tools to produce materials at an unprecedented scale. For leaders and practitioners seeking to understand AI developments and make informed decisions, this flood of information makes it increasingly difficult to separate valuable insights from background noise. And it also forces an important question we must all address: Am I doing everything I can to shine a light on the key issues, or am I only adding to the confusion?

The rapid advance of AI technology compounds these challenges, with new capabilities emerging at a dizzying pace. The internet has become crowded with speculation about AI's future and unverified claims about its capabilities. Making matters worse, AI-generated misinformation has become sophisticated enough to convincingly mimic legitimate sources, voices, and attitudes. What can we do to stay in tune with the topsy-turvey world of AI?

One conclusion I have reached is that the only way forward is to do less. That’s right. Instead of increasing the frantic pace to widen the scope, follow more threads of discussion, and produce more content, perhaps the best approach is to limit the range of materials, ignore areas that fall out of my sphere of influence, and focus my efforts on ways to add insight and create impact.

Rather than trying to consume more information, the trick may well be to become more selective about what voices to listen to. Success in 2025 requires focusing on high-quality, authoritative sources with proven track records in AI delivery. This includes peer-reviewed research, technical documentation from established AI companies, and insights from recognized experts who understand both AI's potential and its limitations. And it means increasing the quality, not the quantity, of the contributions we make.

Not Waving but Drowning

One major challenge facing all digital leaders is the rise of "AI Slop" – the vast quantity of mediocre, AI-generated content flooding our digital channels. This includes countless variations of basic explanations and surface-level analyses that, while technically accurate, offer no meaningful insights. The ease of generating this content has led to a form of digital pollution that makes valuable information harder to find.

But that is not the only issue. The problem of "AI Hype" presents another significant challenge, as vendors and promoters make increasingly extravagant claims about AI's capabilities and potential impact. This overenthusiastic marketing creates unrealistic expectations among business leaders and can lead to misguided implementation strategies. The challenge lies in distinguishing genuine technological progress from exaggerated promises designed primarily to drive sales.

Finally, and perhaps most concerning, is the emergence of "AI Misinformation" – deliberately misleading content about artificial intelligence and its capabilities. Unlike simple low-quality content or marketing hype, this material is specifically designed to confuse or mislead readers about AI technology. Through sophisticated use of AI tools, this misinformation often appears highly credible, making it particularly dangerous for decision-makers who rely on accurate information to guide their AI strategies.

Three Steps Forward, One Step Back

So, in 2025 I'm adopting a much more focused approach to my work that prioritizes depth over breadth. My strategy centres on three key advances, balanced by one strategic retreat.

The first step forward is curating a more selective circle of authentic voices in AI. Taking time to separate the signal from the noise. Rather than following the crowd, I'm identifying thought leaders and practitioners who share substantive insights rather than just trending opinions. This means spending more time with detailed technical blogs, academic papers, and practitioners who openly discuss both successes and failures.

The second advance involves deeper engagement in forums where meaningful AI discussions flourish. I'm shifting away from broad social media platforms to more focused communities where AI leaders and practitioners actively collaborate and remain open to evolving perspectives. These spaces often feature more nuanced discussions about AI's practical challenges and ethical considerations. I’m looking to play my part in facilitating and driving these conversations to bring additional light on the key issues.

The third step forward focuses on delivering tangible solutions to specific problems. Instead of contributing to the welter of high-level AI commentary, I'm committing to sharing documented case studies and practical implementations that address real-world challenges. This means getting my hands dirty with actual code, real datasets, and measurable outcomes. Something I don’t feel that I’m doing enough of right now.

The strategic step back is equally important: I'm deliberately reducing the quantity of my content output. Rather than maintaining a constant stream of AI-related content, I'm focusing on producing fewer, but more insightful pieces that offer genuine value to the community. This means each contribution will be more thoroughly researched, technically sound, and practically applicable.

I’m hoping that this balanced approach reflects a mature understanding that in the rapidly evolving AI field, sometimes doing less can help us achieve more. I guess we’ll see.

What’s your strategy for 2025? How will you separate the signal from the noise? Let me know your thoughts. And whatever it is, I hope it works for you. Have a good one!