Agentic AI is now the talk of the town and changes stemming from it will bring the form of AI support people imagined and witnessed only in movies (link). But what does this mean for businesses? Will AI suddenly appear and be adopted as the new norm across all levels of transaction? Or will it create a period of agonizing evolution for all businesses as well as their customers? 

The tide of change is already in motion and in this post, I want to explore ideas on how to prepare for this tsunami wave.

Change is the only thing that’ll never change for any industry. The challenge is, the rate of change has been only accelerating through the centuries. This reduces the time to adapt existing business frameworks. Even more than the actual changes that will be triggered by the AI solutions themselves, this lack of time will be the greatest challenge for businesses. 

Think about the Industrial Revolution. The steam engine took about 70 years from development to driving major changes in the industry. Thomas Newcomen invented his first machine in 1712 but it wasn’t applied majorly beyond the mining industry in the 1780s. On the other hand, the first realization of early machine learning models can be dated to the early 2010s. However, only 15 years later, even the concept of AI itself has evolved from advanced pattern recognition to automated content creation and there are already several companies of varying sizes replacing their human staff with AI.

People, companies, society, and even governments had several decades to prepare for the change and it still sent through a big enough shockwave to the existing social infrastructure that it was named a revolution; industries were built, tons of jobs were eliminated and more created, cities exploded with people, and the concept of organized labor was created. So imagine how much disruption the AI revolution would bring where the next 5 years’ worth of forecast is considered “long-term”.

Take a look at a few speculative studies below that estimate the impact on the workforce. Any way you look, the impact will be nontrivial for everyone. 

There has always been some new shiny thing in every industry that promised a bright future which rainbows and unicorns. Machine learning, robotic automation, Cloud technology, predictive analytics were all buzz words in the industry at one point. They were the topics of choice in strategy meetings, industry conferences, and webinars. But I can say that while the majority of the organizations ‘adopted’ these technologies, very few successfully transformed their businesses to adapt to a more efficient and productive format. 

If you take healthcare for instance, the electronic medical records have now become the norm in most hospitals, clinics, and health systems. However, there still are processes, practices, or even entire hospitals that still rely more on paper forms, one-off Excel spreadsheets, and emails.

You could literally write a book (or books) about all the root causes that disrupts a smooth transformation. A few common barriers are in the diagram below but from my experience, the biggest challenges are around aligning existing processes with the new technology and sustaining those implementations through staff training and consistent reminders. 

An additional layer of difficulty is that the technology as well as the business environment continues to change continuously. So the successful implementation that was completed a month ago may already be old news and needs to be updated. Keeping up with these changes, redesigning the strategies, and updating educational content are not only difficult for the operation owners but it’s also a huge burden on the staff as well. Change fatigue is real. And ugly. 

So there is a huge change headed your way and it’s big, fast, and continuously morphing. Now what? Where do you start to successfully build a flexible and versatile business model charged by a resilient team culture? My recommended first step is to start with a set of questions to assess your current state. Here are a few starter questions to get your started.  

While it may be tempting to shop for the new shiny things for your company, I’d suggest not diving into that too quickly. The challenge again, is not adoption but transformation. Without the proper infrastructure to support the new AI solutions in the long run, you might end up with a costly experiment that collects dust on a shelf. 

So try starting with the list of questions above. They may be starter questions but they won’t, and shouldn’t, be easy to answer. Keep in mind that digital transformation will most likely not be a one time effort. Creating a continuous improvement culture is a golden standard in every industry but with something as novel as AI that keeps changing on almost a daily basis, there needs to be an even greater emphasis on building that resilient team that can weather the several iterations until new technology is fully immersed into the operating framework.  

The larger the organization the heavier the lift would be to complete a full robust transformation; Strategic and operational alignment from the top of the organization to individual teams, implementation of governing structures, legal and regulatory reviews, blessings from the IT team, training super users, launching change management campaigns, preparing communications, and on and on and on. Depending on the size of the implementation, this list could grow many chapters and subchapters.

Imagine a hospital or health system where every process requires close coordination with several internal stakeholders (i.e. physicians, nurses, social work, etc.) as well as external stakeholders (i.e. insurance companies, referring clinicians and hospitals, post acute care facilities, etc.). Replacing or complementing an existing process with some AI solution will impact the all stakeholders to some degree. Some changes will need aligning and coordinating across multiple organizations. Lack of preparation and strategic alignment might actually result in several versions of the process which will only increase the workload for the staff, rather than simplifying it. These changes are not only unsustainable but it’ll slowly but surely nibble away the momentum of change for your team. 

So even if you might feel like you’re already behind in this AI race, take some time to sharpen your axe before heading into the forest. It’ll make your AI shopping experience much more enjoyable. 

This is probably one of my longer posts but I think it barely scratched the surface of what should and could happen with AI implementation. If you would like to see more in-depth content about any part of the process, please leave a comment below!