AI Topics
| Disclaimer | Urgency |
| Science behind AI | Befriending ChatGPT |
| AI for Product Teams | Internal Use to Improve Everything |
| Marketing AI as a Feature | Risks |
| AI Stories | Terminology |
First full articles on AI will be published through January, 2025
Disclaimer
These articles exist to offer perspectives. They should always be consumed only as perspectives. It is up to the reader to decide how and if to integrate these perspectives with whatever business or personal challenge drove a visit to this site. Given the subject of this group of articles is AI, AI tools have been used to form aspects of what is presented.
ChatGPT wanted me to post this as the disclaimer -- you can choose -- "The views and insights shared in this series of articles about artificial intelligence (AI) are intended for informational purposes only. While every effort has been made to ensure the accuracy and relevance of the content, the fast-evolving nature of AI technology means that certain details or interpretations may become outdated. These articles should not be considered as professional advice or a definitive guide for implementing AI strategies within any specific organization. Readers are encouraged to consult with qualified experts or conduct further research tailored to their unique business needs. The opinions expressed are those of the author and do not necessarily reflect the views of any organization or entity associated with the author."
Urgency
AI is evolving rapidly, much like other transformational technologies in their early years. For perspective, consider the introduction of spreadsheets in the late 70s. For finance analysts accustomed to calculators and ledgers, spreadsheets were revolutionary: they automated calculations, enabled live "what-if" scenarios, and transformed industries overnight. AI holds similar potential. Approaching it with this mindset can help you and your organization move forward confidently. Finance professionals who resisted spreadsheets were quickly left behind—AI is no different.
If there’s an urgency, it’s to uncover how AI can make you a "better you." While this may sound metaphorical, the sooner you identify AI’s benefits, the sooner you can focus on higher-value activities in your role. When an entire team embraces AI, the benefits compound, elevating everyone. While AI may lead to the end of some roles, it often creates new opportunities and new roles. The key is to remember that there’s “always more to do.”
AI frees up time from routine tasks, allowing you to focus on those that often go overlooked. Imagine reversing the 80-20 rule—spending most of your time on the 80% of tasks that rarely receive the attention they deserve. Would this lead to higher-value contributions? To achieve this transformation effectively, the whole team must adopt AI together, ensuring alignment and shared progress. 
Science Behind AI
AI chatbots can often give answers to this question that sound mystical or overly complex, especially from a data science perspective. To help understand how AI works, it's helpful to break it down into simpler terms first. The more you understand, the more comfortable you'll feel using AI and accepting it as the transformative technology it is.
Basic Science Behind Search:
- Break down an article about the Northern Lights into an ordered list of all the words and phrases it contains, along with their physical locations in the document (e.g., line number).
- Break up your AI-like question in the same way.
- Using a vector math approach, generate the list of line numbers in the document that contain the words or phrases from your query.
- The best answer typically starts near where the numbers (line locations) are closest together (e.g., same lines).
This very basic approach to relevance is still used (though much more refined of course) in most text-searching algorithms. It formed the very early foundation of tools like Google search and built up from there. It's not magical, it involves a lot of vector math and statistical algorithms to process the data against a query, something computers can be programmed to do, exceptionally well.
Befriending ChatGPT
Internal Use to Improve Everything
AI for Product teams
Over the last 30 years or so, the number of coders has grown dramatically to accommodate professional needs. Starting below a million in the US in the early 90’s it is estimated there are well over 30 million professional software engineers as we head into 2025. That count does not include the millions and millions of web development tool users managing their own needs, with little formal coding training, relying on tools such as WordPress, HubSpot, Spotify, GoDaddy, AWS to generate the templated code that is needed.
For anyone who has used AI coding tools like CoPilot from GitHub, it is easy to see that AI tools thrive generating code. They are largely semantic language engines after all. Given most coding languages are meant to be semantically unambiguous for a computer to execute the code properly, the sophistication AI embodies to understand and generate ambiguous spoken languages like English, is largely left unneeded. Code generating tools still suffer from garbage-in/garbage out risks (as do AI chat tools like ChatGPT). This is where AI-augmented skills for human operators (you and me) become critical, to get the value you want to realize, and possibly, to preserve the jobs.
For Product managers, the essence of the Product role is the synthesis of streams of requirements (input) to create the output an Engineering team can use to economically build, and a business can take to market to generate revenue. The more unambiguous and consistent the output a Product team can be produce, the more likely coders and sales teams will be able to meet the needs identified. While there is a general risk of homogenization of thought and approach as we become dependent on AI (as there was with spreadsheets in Finance long ago) – the benefit for Product is alignment, consistency and completeness of analysis from the generated artifacts produced over time.
Coders and Product managers are two of the areas most ripe to be transformed through comprehensive adoption of AI. Jobs will change, we'll explore how to migrate your talents to where AI drives them.
Marketing AI as a Feature
Risks
There are several risks to keep in mind when exploring integrating AI into your daily tool set. Homogenization of thought and approach is near top of list and carries pro and con attributes. As we understand the technology, we know AI tools are guided by the language models and datasets they have access to. Using tools like ChatGPT is akin to consulting with 10 different people, but all having graduated from the same business school program. They likely follow similar approaches to most challenges presented. While this creates alignment and consistency, it also narrows the space for innovation and differentiation. As an AI user, you must learn to craft your inputs and questions to challenge the conventional threads of the algorithms, which will widen the diverse insights you gain back. We'll look at key risks to consider, along with their potential mitigations, which is meant to expand your appreciation for how to prepare to be AI-augmented. 
AI Stories
I studied AI in the early 80s at university, where it was an exciting but often elusive topic—promised as the 'next big thing' in tech. Despite my background, it still fascinates me that we've now reached a point where AI is no longer just a promise, but a reality. My new challenge is to build a relationship with AI and leverage its benefits to the fullest.
This article shares some random experiences, some humorous, to help develop comfort with using tools like ChatGPT and CoPilot. I include some of the key takeaways for each:
The Professional Colleague Realization: It took me a few weeks of working with ChatGPT to realize it was designed to interact as a professional colleague. I stopped phrasing my input like a Google search and started treating it more like a conversation in a business meeting with my team. I also began correcting my spelling and grammar errors (even though it’s clear ChatGPT doesn’t mind) because, well, it’s a good habit to cultivate.
- Takeaway: I now have a permanent, no-cost virtual business teammate to help me with my daily work.
- Takeaway: ChatGPT will never ask me about the weather or my family—it’s strictly business.
AI Terminology
Using the term AI (Artificial Intelligence) is often the biggest challenge to understanding what it is. ChatGPT itself describes AI as "the simulation of human intelligence processes by machines, especially computer systems". While that is the goal, to be recognized as a machine that displays the characterstics of human intelligence, it is not intelligent. It can only do what it is designed to do whereas, we all believe, the human brain has that extra ability to be spontaneously creative. We may yet uncover more about how our own 'algorithms' work, but until that happens, AI remains a hugely sophisticated computer system, with oodles of data, complex analytical algorithms, lots of math all driving it -- and an insatiable need to consume computational power.