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 iter­a­tive 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: Rather than being over­whelmed, what does it take to har­ness dis­rup­tive sit­u­a­tions like major inno­va­tion rev­o­lu­tions like gen­er­a­tive AI? What are the 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? 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.

IT exec­u­tive lead­ers can apply to attend the ASUG Exec­u­tive Exchange 2023 Fall Sum­mit (Sep­tem­ber 25 – 27, 2023; in Nashville, TN) here.

Jack Shaw helps lead­ers under­stand the strate­gic impli­ca­tions of emerg­ing tech­nolo­gies. He shares a prac­ti­cal approach to how they can spur inno­va­tion and allow orga­ni­za­tions to fore­see, plan for, and man­age dis­rup­tive change. He inte­grates his decades of exec­u­tive man­age­ment respon­si­bil­i­ties in indus­try, tech­nol­o­gy, and con­sult­ing to speak on Inno­va­tion, Tech­nol­o­gy, and the Future. His expe­ri­ence design­ing, devel­op­ing, and imple­ment­ing emerg­ing tech­nolo­gies enables him to explain lead­ing-edge con­cepts and tech­nolo­gies such as AI, Blockchain, 5G, the Inter­net of Things, Web3, and the Meta­verse in eas­i­ly under­stood terms. Jack has pre­sent­ed over 1,000 keynotes and exec­u­tive forums to over 300,000 top lead­ers and pro­fes­sion­als in 26 coun­tries and every U.S. state.