History may not repeat itself, but it certainly does rhyme. While the implications of generative AI have yet to be fully understood, there is a growing consensus among technology strategists that its impact on the modern enterprise will be both profound and long-standing. In this fast-changing environment, executive experience is a key variable for successfully navigating the next seismic shift in the innovation landscape.
So says enterprise technology futurist Jack Shaw, who will be the keynote speaker at ASUG’s upcoming Executive Exchange 2023 Fall Summit (Sept. 25-27, in Nashville, TN). Over the past several decades, Shaw has been among the few executives and analysts with a front-row seat to observe the disruptions transforming companies and industries across the globe.
From early efforts to harness the machine-to-machine communications capabilities of electronic data interchange (EDI) in the 1980s, through the introduction of the world’s first widely available web browser in the 1990s to the rise of cloud computing—and now generative AI—Shaw has spent his career analyzing the patterns that separate the organizations upended by innovation from those that see disruption as an opportunity to pivot into more profitable pastures.
ASUG spoke with Shaw to gain his insights on what we can learn from previous technology-enabled dislocations to guide the path forward as we enter the era of the generative AI-assisted enterprise.
This interview has been edited and condensed.
ASUG: We’re once again at the edge of a major innovation revolution with generative AI. What does it take to harness these types of disruptive situations, rather than being overwhelmed by them? What have you seen as keys to success?
Shaw: Very early in my career, I understood that innovation is not just about technology. It’s about figuring out what you can do with technology, rethinking how business processes work, and then leveraging technology to implement new strategies that yield better results.
From the early days of EDI and electronic funds transfer (EFT), it was clear the power of technology lay in allowing machines to do things they do well, freeing up humans to excel in other areas. Early movers achieved strategic advantage by recognizing the business benefits of automating functions like accounts payable (AP) and accounts receivable (AR).
Even in those days, there was discussion of what role artificial intelligence could play. The more I learned, the more I realized that—at that point in history—AI was a long way from prime time. I was intrigued, and I kept an eye on it.
Another technological development, however, was about to be unleashed on the business community. For years, we’d heard that government agencies and research universities were sharing information using what they called “the Internet.” It was still an obscure concept, not open to commercial use.
It wasn’t until the early ’90s that the Internet was opened to commercial use. I thought it looked promising but expensive. I remember one company saying, “We can set you up with an Internet account, and it’s only going to cost you $9,000 a month.” It had great potential, but something was missing.
A few months later, I was speaking at a conference. I got there a little early and watched the previous speaker, who said, “We’re going to demonstrate a new piece of software: a graphical web browser called Mosaic.” Five minutes into the demo, I said, “This changes the world. This is it. This will let ordinary, non-technical people use and derive value from the Internet without having to know how to write code.”
Today, we’re having the same conversation about generative AI. ChatGPT set off the same light bulb. This democratized flavor of AI is kicking innovation into another gear because it will put tremendous capabilities into the hands of ordinary people, who are not technical experts.
ASUG: What are some implications for innovation at the modern enterprise?
Shaw: For decades, one way of thinking had it that technology—especially emerging technologies—was the bailiwick of the IT department. Businesspeople, including senior executive decision-makers, middle managers, and first line staff handling tactical and operational activities, waited for the technology team to bestow upon them some new tool or approach.
Historically, new solutions or projects introduced by the IT team often did not work well to meet business needs. We didn’t spend much time talking about it. And the reason for that was that technology people didn’t understand the business, and businesspeople didn’t relate to technology.
The lines of communication are much better today. That’s good because disruptive technologies are emerging more frequently and evolving more rapidly. The pace of technology-enabled change is accelerating.
In response, organizations—and society at large—have crossed two major bridges over the past decade or so:
- IT and the non-technical workforce work together much earlier and more effectively.
- Organizations are implementing systems and redesigning processes and business models in a more iterative fashion, thanks to concepts like DevOps and DevSecOps.
We’re taking it one bite at a time, and that gives us the option to move toward what I call “dynamic digital transformation.”
ASUG: How do you define dynamic digital transformation, and how can organizations incorporate this process into their strategic planning?
Shaw: Dynamic digital transformation is not a project or even a series of projects where teams commit to a statement like, “This year we’re going to transform this process. Next year we’re going to transform this other process.”
Digital transformation is continuous. It’s ongoing and should be part of the strategic planning. When it comes to planning for the future, there is a sweet spot depending on the size and complexity of most organizations’ size and strategy—between two and three years to perhaps five to seven years.
As opposed to sitting down annually for a couple of weeks to make updates and plans for the following year, leaders should be continuously monitoring the external environment for key economic, industry and technological factors. Too much happens too fast to do this just once a year. Digital transformation needs to be dynamic. Organizations should be continuously monitoring the environment, updating plans, and setting goals to achieve their overall strategy.
This should be ongoing in the same way that non-core functions like human resources and finance have become ongoing processes. Organizations do not hire an HR leader to recruit only a few people; they don’t hire a finance team only to file taxes at the end of the year.
Dynamic digital transformation should also be a dedicated responsibility. In a small business, it could be as focused as a single, appropriately located individual. In a larger business, it should be a unit, one that continuously interacts with other units as HR and finance interact with other operational units, from sales to marketing to manufacturing and shipping.
ASUG: What are the keys to navigating generative AI?
Shaw: I recommend that enterprises proceed on two parallel paths. The first is to address the immediate, short-term opportunities and challenges associated with this technology. Executives have to ask themselves, “How can our employees, from the CEO to front-line people, leverage its potential in a responsible manner?”
Leaders are especially excited about the technology. 85% of senior executives have at least put their hands on ChatGPT or another generative AI tool, like Bard from Google, and played with it. Interestingly, the middle management-level staff (50%) and rank-and-file team members (15%) are more reluctant. I’ve been telling executives to look at how individuals can use generative AI tools to improve productivity and the quality of their results.
Parallel to that, leaders must determine how to effectively use AI tools across the enterprise technology stack. SAP is already incorporating increasingly sophisticated forms of AI into its main enterprise resource planning (ERP) systems.
Other forms of AI can enable more sophisticated use of machine learning to do advanced data analytics, offering predictive analytics. These technologies will play an important role in defining which markets are growing and over what period of time, contrasting with those markets that are not growing as rapidly or possibly even shrinking. Technology can help us understand why. Analytical detail is not the realm of generative AI so much as data analytics and knowledge-based expert systems that can aid organizations across a range of important processes.
ASUG: How do you envision the future of the enterprise technology space?
Shaw: I’ve never been more excited. There are so many technology-enabled trends advancing rapidly. We’re entering a new supercomputer era that will leverage “exaflop” technology, with machines able to calculate at least one quintillion floating-point operations per second.
Even in the ’90s, supercomputer performance—as distinct from regular mainframe performance—was measured in megaflops, or millions of floating-point operations per second. A quintillion is a million trillion. We’re also on the cusp of quantum computing. The technology is already being tested; we may see offerings by the early 2030s. We’re literally going to have billions of times more computing power than we’d ever previously imagined. The vast majority of that computing power will be utilized to deliver AI capabilities and functionality far beyond what most people are able to envision.
It’s not going to be The Terminator, with robots coming out to slaughter us. It’s going to allow for more innovation than we’ve ever been able to imagine before. When you integrate these capabilities with enhancements of technologies already in use—blockchain, the Internet of Things (IoT), augmented and virtual reality, 3-D printing, wireless communications—there are no limits to the possibilities.
We’re no longer going to be constrained by the capabilities and functionalities of our technologies. We’re only going to be constrained by our imaginations.