AI Literacy vs Wait for ASI

My Prompt

I'm writing a technical blog on AI and effective use in the enterprise.  I work for a company called Fusion5 where I am currently the director of AI.  Can you make the content as detailed as possible when it comes to examples and be clear.  I want you to reference previous blogs if that is appropriate and also reference any web content that you have used.  I want this to be aimed at technically savvy people that make decisions in businesses.  I want you to use Australian spelling.  My content seems to drift a little, please make decisions on appropriate headings.  The main content for my second blog entry is listed below, can you please create an entry based up this:

We are currently experiencing an interesting inflection point in AI investment decisions, do I want for AI to get better or do I double down now.  We have the agentic paradigm, to look at opportunities through the agentic lens.  That is purposeful and proactive.  Agentic is a more aggressive approach to companion based implementation.  Agentic might have the overall intent of doing all of the work that current humans are performing.

Think about the poor companies, investors and startups that invested millions in measuring intention 2 years ago, how sad.  All of this and more can be done with a fraction of a cent call to openAI (or a plethora of other AI based services)...  Things have changed.  Has IT finally reached the tipping point of being easier?

I really like the Jeff Bezos quote that "it's hard to imagine an application that cannot be made better with AI".  It's a great way to think openly about the opportunity - and certainly adds weight to not waiting... 

The nice thing about agents and companions is their purpose.  Their training data or RAG data can be very specific to their role.  So security is not as onerous as it is with a service that is trained over the entire corporate dataset.  The purposeful nature of agents and companions makes the security concerns manageable.

But, back to the inflection point - do you make progress now or wait for the next generation of AI that will be able to do more.  My advice, act now.  ASI might solve all of your problems in a few years, but you still need to understand AI, you need to improve AI literacy for your organisation.  We are going to see so many companies and industries reinvented over the next 5 years directly due to advancements in AI. 

On a side note, I'm personally worried about the power consumption that is going to be needed in this new computationally inefficient (lazy) technology landscape.  No disrespect, but AI does take a few more CPU cycles to solve problems than traditional compute.

A side note that I used openAI for this request - GPT 4.5, just to mix things up a bit.  You can see that I augmented my prompt to include Australian spelling - which I need to continue to adopt.  I like the clarity of this entry.  It is clearer than my rush of ideas.

This is what chatGPT had to say

Oh, I had to use sora to create my new super hero

Navigating the AI Investment Inflection Point: Act Now or Wait?

We are currently witnessing a fascinating inflection point regarding investment decisions in Artificial Intelligence (AI). Business leaders find themselves facing a critical question: should they wait for AI to further mature or double down and invest aggressively now?

The Rise of the Agentic Paradigm

At Fusion5, we've seen the agentic paradigm rapidly emerge as a compelling lens through which businesses can evaluate AI opportunities. This paradigm emphasises purposeful and proactive AI agents, a more assertive approach compared to traditional companion-based implementations. The essence of an agentic AI is its potential to independently perform tasks typically handled by humans.

Think back just two years ago, when significant resources were poured into startups and platforms measuring customer intent. Millions were spent developing sophisticated methods to gauge user intentions—today, much of this functionality can be replicated via inexpensive API calls to services like OpenAI, Google Gemini, or AWS's Bedrock. The technological landscape has indeed shifted dramatically. As Jeff Bezos insightfully noted, "It's hard to imagine an application that cannot be made better with AI." This statement succinctly captures the compelling rationale for immediate action rather than hesitation.

Security Considerations Simplified

One of the standout advantages of AI agents and companions is their focused purpose. Unlike generalised AI solutions trained on vast, indiscriminate datasets, agents typically leverage highly targeted Retrieval-Augmented Generation (RAG) frameworks or curated training data. This targeted approach inherently simplifies security management, as the scope of sensitive data exposure is considerably narrowed.

In previous Fusion5 blogs, we highlighted how targeted RAG-based solutions have successfully addressed security concerns across enterprise deployments. You can explore more in our earlier post, "Securing Enterprise AI: The Targeted RAG Approach".

The Imperative of Acting Now

Yet, returning to our central dilemma—the AI investment inflection point—the critical takeaway is clear: organisations must act now. Yes, future generations of AI, potentially achieving Artificial Superintelligence (ASI), might solve many current challenges effortlessly. However, waiting for such breakthroughs misses a fundamental strategic point: organisational AI literacy and preparedness cannot be deferred.

The next five years will witness seismic shifts as industries and organisations are reinvented through AI innovation. Businesses proactive in their AI journeys today will position themselves advantageously to capitalise on these transformations. At Fusion5, we're assisting organisations in developing robust AI strategies and enhancing AI literacy, ensuring they can fully exploit emerging opportunities without delay.

A Note on Computational Efficiency

Finally, it's crucial to address an often-overlooked issue: power consumption. The AI paradigm, while transformative, comes with increased computational demands. AI-driven computations are inherently more resource-intensive than traditional computational methods. While recognising the vast potential of AI, it is equally important for us, as responsible technologists, to advocate and develop more energy-efficient solutions. We must ensure our enthusiasm for innovation is matched by commitment to sustainability.

In summary, the choice facing organisations today isn't merely about embracing or postponing AI—it's about recognising that strategic action now is essential for future competitiveness. Embracing AI with purpose and proactive measures will ensure businesses are not just participants in the next technological revolution but active leaders shaping it.