How is the AI hype at your organization looking? Are you re-evaluating AI investments moving into the new year?
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Significant changes have occurred since 2023, particularly with the launch and subsequent adoption of ChatGPT. In my opinion, the most significant advancement for enterprises has been the Microsoft and OpenAI partnership, which seamlessly introduced Co-Pilot to businesses without additional costs or effort.
While it’s still early days, more and more companies are discovering intriguing use cases, and individuals are sharing their experiences. This growing confidence is encouraging other enterprises to explore AI solutions.
At our organization, we’ve implemented a GenAI strategy and established an AI council to navigate these uncertain times. Our current focus lies in enhancing customer service, chatbot and technology.
We are thrilled to share the excitement that is palpable at all levels and across all business and operational areas. We have all embraced the use of ChatGPT as our Copilot in our daily operations.
It’s important to highlight that the success we’ve achieved, which has exceeded our expectations, is the result of individual effort and not merely the outcome of following any specific training, coaching, or AI guidance. There’s no doubt that AI has become an integral part of our daily tools, even without formal adoption.
We’ve come to understand the challenges that come with “Prompt Engineering,” even when clean and available data is at hand. It appears that for achieving great results, the focus on “Promoting” could make the difference.
Yes AI hype among leaders are real.
Let me give you an example : My organization head was like "lets implement Microsoft Copilot?
My question was why? and where we would be using it?
The question lead to a debate & discussion in the company "What is the use-case"? That lead to our internal - "Data Management" , "Data Security" , "Data Quality" and most important
- What Process it should be implement.
- What would be the change management process.
Hence the approach we are taking are Shiny Object vs Real outcome.
We’re not too hyped at buying vs building internally .
Agree on the preference for investing in buying instead of building. I’ve seen too much legacy tech plaguing large corporations that built their own custom solutions, with significant downtime despite high maintenance costs and an increasing gap in capabilities compared to more current third-party solutions. Worst of all, replacing legacy systems is a nightmare- primarily because of sunk cost fallacy among decision-makers, and/or resistance from the senior stakeholders that sponsored the DIY build originally. And if you can get past that, from a technical standpoint there tend to be significant challenges integrating the new tech with older systems that remains (legacy, custom tech often used point-to-point integration…)
Agreed 100%. The counter argument is that integration difficulties can lead to inefficiencies but that also exists with DIY vs DIFM solutions. I’ve seen far too many problems with certain BigTech platform’s own products during investigations and audits that may have been alleviated if it was initiated as a Cloud based, out of box solution to begin with, with less room for conflicts of interest and industry leading standard governance.
Educate! Establish AI Use Policy! Avoid feature Myopia!
The Double-Edged Sword of Technology
AI has limitless positive aspects to world advancement. Yet, Technology often evokes a love/hate relationship. In today's world, the only way to avoid AI is to live on an isolated island with no connectivity, somehow evading even satellite coverage.
Investment in Human Learning
First and foremost, prioritize "Human Learning." Develop a comprehensive onboarding program to clearly outline what is acceptable internally and what is not. Trust factors online are currently very fragile. What Intellectual Property are you sharing online to seek refinement? Who may have sniffed out that data? Have you read every Terms and Conditions document to find out everything that is permitted to be shared verse what was not?
The Human Factor in Cybersecurity
A staggering 95% of all cyberattacks are caused by human error. This statistic highlights the critical role of human factors such as lack of attention, impulsive actions, and ignorance in the use of technology. In business, there's a dangerous assumption that everyone understands how to responsibly use the tools at their disposal, often without a feedback system to verify this understanding. Technology Education for business continuity and cyber security is a continuum.
The Real Threat: Human Error Over AI
The fear of AI becoming "evil robots" is misplaced; human error will remain a far more pressing issue. Ignoring AI is not a viable option—it's an unstoppable force. AI relies heavily on algorithms and the mathematical stability of problems. It is also extremely content-dependent, with giants like Google, Microsoft, FB, benefiting from decades of user-provided data (as outlined in those T&C's no one reads!).
Embracing AI
In reality, AI will soon be ubiquitous. Whether we like it or not, AI has been influencing our lives for over a decade. If you've ever used Google, a map app, driven a car built since 2020, shopped on Amazon, used a smartphone, or engaged with social media, you've already been interacting with AI. Embracing AI is not just inevitable but essential for staying relevant and secure in the modern world.