AI & The North American Confusion about Productivity
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AI & The North American Confusion about Productivity

The current global feeding frenzy around the topic of artificial intelligence (AI) has sparked a "Gold Rush" mentality among many businesses and an “Arms Race” among technology vendors both of which are promising the potential for increased productivity and improved customer service.?

However, a closer examination on how many (not all) organizations are initially leveraging AI reveals that this rush is more often driven by a narrow focus on short-term gains, often at the expense of long-term customer satisfaction and the quality of service. The AI Gold Rush, much like its historical namesake, is initially proving to be more about the frantic pursuit of profit than the promise of progress. In a landscape dominated by flashy headlines touting AI's potential to revolutionize customer service, a more insidious truth often lurks beneath the surface. The emphasis on automation and self-service, while presented as enhancements, often masks a thinly veiled agenda of cost reduction.?

This echoes the recent "shift left" movement in the service desk industry powered by early chatbots and self service portals, a business model that often prioritized deflecting support requests to lower-cost channels, rather than genuinely improving the customer experience. As we delve deeper into this AI-driven landscape, it becomes increasingly clear that the pursuit of increased profits by cost-cutting is often superseding the noble goal of delivering exceptional service.?

The reality is that this should not be surprising since we have seen the same scenario play out many times in history when new technology catches the imagination and the attention of the venture capitalists and short term focus of shareholder priorities.

Despite the technology’s true ability to make a difference for the good and fulfill the many promises of the marketing hype, profit and or advantage is often the primary motivator for its initial deployment. What we tend to do though is use very positive words to sugar coat a much less virtuous set of goals.?

Currently the key word that is the focus and center of the AI revolution is the word “Productivity”

But to quote a famous line from the movie Princess Bride -? Inigo Montoya: “You keep using that word. I do not think it means what you think it means.”?

To illustrate this point I would like to share an important AI related article that was published by CNBC last week.?

Corporations looking at gen AI as a productivity tool are making a mistake

?https://www.cnbc.com/2024/05/31/corporations-looking-at-ai-as-a-productivity-tool-are-making-a-mistake.html

?

As a disclaimer I actually fully agree with the premise and the key messages of this article.

However, the article's use of the term productivity in the title reveals a misunderstanding of Lean principles rooted in a North American context. For many when they hear the term "Lean" it is often misinterpreted and applied as a means to reduce headcount, slash costs, and maximize profits, rather than the true essence of Lean, which is to eliminate waste and create value for customers. This historical misinterpretation, prevalent in the 1980s and persisting to this day, has unfortunately led many to associate Lean with job losses and negative impacts on the workforce, rather than its intended purpose of improving processes, quality, and efficiency while respecting and empowering workers.

The actual Lean definition of productivity defined in the Toyota Production System (TPS) focuses on balancing all three dimensions of quality, speed and cost.

Productivity =? Increased speed of output while reducing waste, level of effort and improving quality. Ultimately it focuses on delivering value to customers by leveraging our resources in the most effective way possible.

At Pink Elephant, our courses emphasize that Lean isn't about "doing more with less," but rather about strategically allocating resources to high-value work while eliminating waste. In essence, it's about working smarter, not harder. The messaging of a truly successful AI transformation should mirror this principle, focusing on how AI can augment human capabilities and streamline processes for greater overall impact.

While these observations are interesting, what is important is that the message of this article is accurate and important but the use of the term “productivity” in this context perpetuates a historical mis-use of this term.

?The title should be more accurately written as “Corporations looking at gen AI as a cost cutting tool are making a mistake”

?With this context here are some important accurate statements to consider:

“The research from Genpact and HFS showed that business leaders are dedicating up to 10% of their IT budgets to gen AI projects. But factors such as data governance concerns, talent shortfall, and proprietary data accessibility have contributed to low spending and have widened the barrier between pilot and production”
?“AI is transformational and requires a comprehensive revaluation of current business processes, data strategies, technology platforms, and people strategies, Pallath said. “Implementing AI effectively necessitates simplifying and revamping business processes with an AI-first mindset,”
"Establish a clear view of responsible AI: Another good practice is to establish a company culture of responsible AI. Companies need to start their AI journey with a clear view of responsible and ethical AI considerations, and ensure they are understood across the organization,” Menon said.”
?“Effective change management and governance are crucial to ensure that the entire organization is prepared for and engaged in this transformation.” What often happens, he said, is that employees worry more about AI’s impact on their jobs, rather than how they can leverage the technology to help them work smarter, thereby hindering the necessary changes in process to make AI”

This last point is not surprising when the title of this article indicates that most organizations are looking at AI as a cost cutting? and staff reduction strategy. Which is again repeating the failed profit focused approach to adopting the Lean Manufacturing principles in the 1980s. I recently read a related article about the impact of AI on the software gaming industry. The author stated that big game studios are using AI like corporate Ozempic. A weight reducing strategy that they would rather not talk about in public.?

While this is a sad reality for many people there is no denying the impact of this most recent but possibly most disruptive technology disruption in the past several decades.? AI adoption will have both positive and negative implications for the world we live in and like all previous disruptions not everyone will be personally benefited from this change.

A recent discussion with a long term friend of mine David Messineo about the impact of AI https://www.dhirubhai.net/posts/davidmessineo_ai-genai-ocm-activity-7203859142975877120-biEt?utm_source=share&utm_medium=member_desktop

brought to mind this quote I heard during the pandemic.

“We are all in the same storm but we are not all in the same boat!

Some boats will rise and many others will not.”

This statement highlights the stark contrast in the impact and benefits of AI between those who have the means and access to it, and those who do not. This disparity exists at individual, organizational, and macroeconomic levels. However, it is equally important to acknowledge that there are numerous positive and compelling reasons for individuals and organizations to consider adopting and adapting AI technologies.

While the uneven distribution of AI's advantages is a valid concern, it should not overshadow the potential benefits. Responsible and ethical integration of AI into various spheres of life could lead to advancements in fields such as healthcare, education, and sustainable development, ultimately improving the quality of life for all. However, continuing with the key principle of Lean we need to do this while equally respecting the value and importance of the people doing the work. Addressing the existing disparities and ensuring equitable access to AI should be a key priority to prevent further widening of the digital divide.

If you are interested in reading more I would recommend a recent article from my colleague Robin Hysick ?

Artificial intelligence (AI) isn't the future; it's now. Are you ready?

https://www.dhirubhai.net/pulse/artificial-intelligence-ai-isnt-future-its-now-you-ready-robin-hysick-9qvve/?trackingId=6cHr%2BM%2BASleo4GCB%2Baehdw%3D%3D

These and other key messages related to successful AI transformations are the topics of several of the sessions at our annual conference at Pink25 that I and several other speakers are hoping to share with you.?

https://www.pinkelephant.com/en-US/Pink25/program

Troy’s Thoughts What Are Yours?

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