Down­load the full inter­view here.

Few peo­ple have wit­nessed the util­i­ty industry’s dig­i­tal trans­for­ma­tion as inti­mate­ly as Gary Hayes. Start­ing his util­i­ty career in 1980 build­ing and hand­ing off paper work orders, and lat­er, near­ly a decade as a util­i­ty CIO, before join­ing Cognizant’s team in 2020 where he now guides util­i­ties through the very trans­for­ma­tions he once led from the inside.

As Chief Solu­tion Enable­ment Archi­tect at Cog­nizant, Hayes helps util­i­ties move beyond ​“trans­ac­tion­al, step-by-step” sys­tems toward ​“intel­li­gent, out­come-cen­tric” oper­a­tions that fun­da­men­tal­ly rethink process­es rather than just dig­i­tize them. It’s a shift from ask­ing, ​“How do we com­plete this process faster?” to ​“How can we pre­vent an issue before it hap­pens and/​or resolve it in real time?”

His ​“Util­i­ties of the Future” frame­work — cre­at­ed over a decade ago and peri­od­i­cal­ly revised since — maps this evo­lu­tion through four stages: from orga­ni­za­tion-cen­tric to enter­prise-cen­tric to out­come-cen­tric to intel­li­gent systems.

“The vision remains,” he says. What has changed is how much clear­er that vision has become, as tech­nolo­gies like arti­fi­cial intel­li­gence and data fab­ric have evolved from con­cept to capability.

ASUG sat down with Hayes to talk about the cur­rent state of soft­ware imple­men­ta­tion in util­i­ties orga­ni­za­tions, the role of lega­cy data, and util­i­ties build­ing trust with AI processes.

This inter­view has been edit­ed and con­densed for length and clarity.

Q: Your Util­i­ties of the Future dia­gram out­lines the shift from orga­ni­za­tion-cen­tric trans­ac­tion­al sys­tems to intel­li­gent, out­come-cen­tric oper­a­tions. How do you define what it means for a util­i­ty to be tru­ly intel­li­gent today, and what dis­tin­guish­es that from sim­ply being digital?

I start­ed my career in 1980 at an Okla­homa util­i­ty. I remem­ber after a tor­na­do or sig­nif­i­cant storm, it would require a lot of time, effort, and paper­work, plus input into a vari­ety of dif­fer­ent paper files or com­put­er sys­tems to under­stand the cost. I was on the project team that imple­ment­ed core SAP in 1995. After our first major storm fol­low­ing the SAP go-live, I was able to query the infor­ma­tion dai­ly in SAP and get reports on the impact of the storm right after the event — no paperwork!

But what if a util­i­ty could lever­age AI to plan, man­age, and dynam­i­cal­ly report through­out these events? If AI and oth­er insights pro­vide a his­tor­i­cal view back in time to data and infor­ma­tion, we should expect AI to lever­age his­tor­i­cal and real-time infor­ma­tion dur­ing the event, pro­vid­ing insights on actions that will reduce the recov­ery time. Resources can be man­aged more effec­tive­ly and effi­cient­ly through data-dri­ven visu­al­iza­tions and rec­om­men­da­tions to the oper­a­tional recov­ery cen­ter, dig­i­tal­ly enabling the process to assist in storm recov­ery. We’ve seen com­po­nents of these solu­tions at util­i­ties being used in severe weath­er and wild­fire prediction/​prevention. AI solu­tions are begin­ning, and will con­tin­ue, to per­me­ate day-to-day util­i­ty busi­ness process­es — oper­a­tional, cus­tomer, finan­cial, and others.

To me, this trans­for­ma­tion has been ongo­ing, from the paper-based/­main­frame sys­tems we were using when I start­ed, to the oppor­tu­ni­ties we have today. While we knew tech­no­log­i­cal inno­va­tions were com­ing, the lev­el of sophis­ti­ca­tion and the scale of pos­si­bil­i­ties are still impres­sive. We now have intel­li­gent and respon­sive capa­bil­i­ties that can act on real-time and his­tor­i­cal infor­ma­tion to advise, assist, and/​or per­form day-to-day work, help­ing util­i­ties achieve both increased effi­cien­cy and cus­tomer sat­is­fac­tion at a crit­i­cal time of change in the indus­try. This recent cycle of trans­for­ma­tion, cou­pled with the con­tin­u­ing expan­sion of the ben­e­fits of oth­er invest­ments — such as smart grids — is accel­er­at­ing us to the ​“Dig­i­tal and Intel­li­gent Util­i­ty of the Future.”

Q: Some orga­ni­za­tions are still tran­si­tion­ing between that inte­grat­ed and intel­li­gent place. Where do most util­i­ties sit on that matu­ri­ty curve right now, and what typ­i­cal­ly holds them back from pro­gress­ing further?

You always see pio­neer­ing lead­ers. Lead­ers are the ones who have intro­duced enter­prise-wide dig­i­tal oper­a­tional man­age­ment tools, advanced ana­lyt­ics dri­ving inno­v­a­tive asset man­age­ment and sys­tem enrich­ments, inno­v­a­tive cus­tomer pro­grams. The list goes on. And, it doesn’t have to be a big com­pa­ny; small com­pa­nies are often lead­ing in these areas. We also see the focus, speed, and inno­va­tion com­mit­ments to trans­form the com­plete foot­print of the util­i­ty from oper­a­tions to cor­po­rate func­tions. ​“Inte­grat­ed, intel­li­gent, and inno­v­a­tive” becomes the tar­get. The chal­lenges: Is this the right time? What are the mov­ing fac­tors — reg­u­la­tors, investors, cus­tomers, tech­nol­o­gy? But we do see increas­ing momen­tum in real­iz­ing the poten­tial of accel­er­at­ing these capa­bil­i­ties. I do not want to infer that every­one is at the start­ing line, but I would prob­a­bly say many are.

At Cog­nizant, we com­mit­ted a $1B invest­ment in the devel­op­ment of AI solu­tions to address chal­lenges and oppor­tu­ni­ties across the foot­print of many indus­tries. And any­one watch­ing us since we made this com­mit­ment in 2023 has seen how we pur­sue and deliv­er AI solu­tions for impact; not just for technology’s sake, but to trans­form the way peo­ple, orga­ni­za­tions, and tech­nol­o­gy can shape the future. 

We are active­ly devel­op­ing and deliv­er­ing AI pro­to­types and solu­tions, both for our inter­nal util­i­ty ref­er­ence and accel­er­a­tor frame­works, as well as for select util­i­ties and ener­gy com­pa­nies. Our col­lab­o­ra­tion with SAP is dri­ving tran­si­tions through S/4HANA native inte­gra­tion, data fab­ric, and BTP solutions.

While the next wave of trans­for­ma­tion will not hap­pen with a mag­ic wand, cloud-based plat­forms, data fab­ric, and AI capa­bil­i­ties form the essen­tial ​“mag­ic” foun­da­tions of the ​“Util­i­ty of the Future.” The com­bi­na­tion of tech­nolo­gies has already posi­tioned us at the fore­front of the AI dig­i­tal work­mate era.

At the same time, the next gen­er­a­tion of employ­ees is enter­ing the work­force with the expec­ta­tion of intu­itive, insight­ful sys­tems. With­out them, orga­ni­za­tions risk strug­gling to attract and retain top talent.

Q: How are util­i­ties, and specif­i­cal­ly SAP cus­tomers, using ele­ments like data fab­ric and S/4HANA to move beyond tra­di­tion­al ERP and enable real-time, insight-dri­ven decision-making?

The first moves were sig­nif­i­cant­ly around data. It’s been with­in the last five to 10 years where you see a sig­nif­i­cant jump in the way that util­i­ties lever­age infor­ma­tion in real time — not just with SAP, but with meter man­age­ment sys­tems, grid sys­tems, dis­tri­b­u­tion man­age­ment sys­tems, and more heav­i­ly data-dri­ven tech­nolo­gies. This was also enabled by the evo­lu­tion of cloud and oth­er tech­nolo­gies sup­port­ing increased capa­bil­i­ties to ​“lever­age and learn” from the data gath­ered. You must make sure your orga­ni­za­tion has, or is ready to, embrace and exploit these rapid­ly advanc­ing solu­tions. Tech­nol­o­gy will con­tin­ue to trans­form, and our talent/​skills must also trans­form to meet the possibilities.

Util­i­ties are posi­tion­ing to achieve this next trans­for­ma­tion­al step, and some are well on their way. But the catch is, while we can make more data and infor­ma­tion avail­able, there’s also the chal­lenge of how you con­sume the vol­ume of infor­ma­tion. How can we accom­plish tasks util­i­tiz­ing SAP’s and oth­er part­ners’ dig­i­tal and AI appli­ca­tions? What does this mean? If your job today is on the asset side, the cus­tomer side, or the finance side, you can’t go to three, four, five, or more dif­fer­ent screens to do your work in the future and be effec­tive or effi­cient. This is where SAP’s dig­i­tal capa­bil­i­ty assists users in quick­ly visu­al­iz­ing, com­pre­hend­ing, and receiv­ing insights to accept the rec­om­mend­ed AI action, to acknowl­edge the actions tak­en for clo­sure, or aware­ness that the issue was cleared by AI. This is the con­tin­u­al chal­lenge and AI goal: to improve the users’ abil­i­ty to exploit the ben­e­fits of this busi­ness trans­for­ma­tion journey.

As util­i­ties adopt these dig­i­tal tech­nolo­gies, there’s still going to be a learn­ing curve. Cog­nizant has accel­er­at­ed sup­port­ing and assist­ing users in this new dig­i­tal expe­ri­ence. We are lever­ag­ing enablers like SAP WalkMe, the ​“sher­pa” that can guide users through dig­i­tal learn­ing path­ways, so users are not only ready for the trans­for­ma­tion, but they can also deliv­er results as they learn. This is how dig­i­tal solu­tions help solve prob­lems much dif­fer­ent­ly than in the past.

At Cog­nizant, we have also pre­pared, and we’re ready to lead our cus­tomers in their dig­i­tal trans­for­ma­tions. Through our AI invest­ments, SAP cer­ti­fi­ca­tions, and trans­for­ma­tion of our work­force and strate­gic part­ner­ships, we’re well posi­tioned to help com­pa­nies nav­i­gate and be suc­cess­ful through this journey.

Q: What does an effec­tive data fab­ric archi­tec­ture look like in a util­i­ty con­text, and how does it rec­on­cile lega­cy SAP and non-SAP environments?

It’s not that there will only be one data fab­ric. You’re going to have SAP’s data fab­ric as well as oth­er exter­nal source data gath­ered in SAP’s data fab­ric. For enter­prise busi­ness solu­tions, SAP will be your core data fab­ric inte­grat­ing data from oth­ers. It could also be a source sup­port­ing oth­er busi­ness or oper­a­tional data fab­rics, whether in AWS, GCP, or Azure sup­port­ing oth­er sys­tems and/​or ser­vices. The approach is gen­er­al­ly depen­dent on the organization’s archi­tec­ture and strategic/​operational objectives.

In terms of util­i­ties, many lever­age the SAP oper­a­tional, cus­tomer, busi­ness, employ­ee, and oth­er func­tion­al­i­ty with the oth­er tech­nolo­gies sup­port­ing sys­tem con­trol, meter­ing, advanced teleme­try, mobil­i­ty, the list go on. These solu­tions will also con­tin­ue to evolve, pro­vid­ing acces­si­bil­i­ty to nec­es­sary process data via tra­di­tion­al data inte­gra­tion lay­ers and/​or fab­ric archi­tec­tures to solutions.

The goal of pro­vid­ing user per­sonas with a dig­i­tal expe­ri­ence is that it allows them to work more effec­tive­ly and effi­cient­ly. This also includes the abil­i­ty to lever­age AI-enabled solu­tions. The bot­tom line is that data fab­rics are the sources to enable all these capabilities.

Q: How does design­ing around per­sonas change the way orga­ni­za­tions build and gov­ern SAP process­es, espe­cial­ly when field, plant, and back-office users have such dif­fer­ent needs?

The real­i­ty is, util­i­ties deal with this today, but they’re deal­ing with a very defined and con­fined rule­set, and via a stan­dard or cus­tomized trans­ac­tion and/​or reports. There are oth­er options that improved the pre­sen­ta­tion lay­er, such as Work­zone and Fiori, which improve user expe­ri­ences by bring­ing addi­tion­al rel­e­vant infor­ma­tion based on the ​“user pro­cess­ing respon­si­bil­i­ty.” As an exam­ple, a Cus­tomer Billing Spe­cial­ist. Ini­tial­ly, this involved learn­ing and know­ing how to look across the SAP I‑SU and oth­er mod­ules to rec­on­cile a dif­fi­cult billing issue. The spe­cial­ist had to tra­verse the data through trans­ac­tion. But now with Work­zone and Fiori, the nec­es­sary infor­ma­tion is brought to the spe­cial­ist. This may also have rec­om­mend­ed actions incor­po­rat­ed into Workzone/​Fiori and automation.

The per­sona ques­tion is: what do you need to do your work? And are you autho­rized to access the trans­ac­tion and under­ly­ing data? If yes, then a series of trans­ac­tions, a pre­sen­ta­tion lay­er, and/​or a report would also be made avail­able to you. As men­tioned, Fiori offered a wel­come user improve­ment. But some­times you may have to call a friend to pro­vide you with addi­tion­al insights to rec­on­cile your or the customer’s ques­tion. Many of those ques­tions end up in some kind of cus­tom inte­gra­tion, addi­tion­al func­tion­al­i­ty, or data fabric/​database integration.

Future per­sona-based capa­bil­i­ties must still ensure the rules relat­ed to acces­si­bil­i­ty to this infor­ma­tion. Lever­ag­ing your persona’s acces­si­ble AI func­tions will allow you to ask AI the ques­tions that are with­in your autho­riza­tion, and it will pro­vide you with the appro­pri­ate and com­pli­ant response, thus enabling you to be more effi­cient and effec­tive in your work. This is the val­ue oppor­tu­ni­ty for AI: to inter­ro­gate that data and pro­vide options or a rec­om­men­da­tion. You’re gath­er­ing insights that can be cor­re­lat­ed through expe­ri­ences and AI mod­els that will tell you, ​“Here are your options,” or ​“Here’s the action you need to take,” or ​“Actions resolved via AI” that are with­in your persona’s respon­si­bil­i­ty aware­ness and tracking.

As an exam­ple, Cog­nizant offers an enter­prise AI solu­tion, Case Man­age­ment, that resolves util­i­ty billing errors at scale. We all under­stand the impact and impli­ca­tions of billing errors. This is typ­i­cal­ly man­aged by a billing spe­cial­ist and/​or man­ag­er. AI reviews and iden­ti­fies the billing errors, then ini­ti­ates appro­pri­ate automa­tion to suc­cess­ful­ly process the required action. It will also pro­vide guid­ed, data-dri­ven rec­om­men­da­tions for teams to resolve the excep­tions, if need­ed. This AI-dri­ven solu­tion will soon be avail­able on the SAP Store. It was devel­oped from our team’s deep expe­ri­ence deliv­er­ing billing solu­tions in util­i­ties, com­bined with our Cog­nizant inter­nal AI initiative.

The solu­tion secured a top-two rat­ing among 21 part­ners in the SAP glob­al Hack2Build event. And in August 2025, the Case Man­age­ment AI Agent for SAP offi­cial­ly earned the Busi­ness AI Cer­tifi­cate. This demon­strates our com­mit­ment to SAP’s stan­dards for secu­ri­ty, com­pli­ance, and data pri­va­cy. In addi­tion, the cer­ti­fi­ca­tion reflects Cognizant’s align­ment with SAP’s AI Respon­si­bil­i­ty Prin­ci­ples, ensur­ing that our solu­tion is not only inno­v­a­tive but also eth­i­cal, trans­par­ent, and trust­wor­thy in its appli­ca­tion of AI.

Q: Util­i­ties have been appre­hen­sive about AI because of accu­ra­cy, secu­ri­ty, and pri­va­cy. Are atti­tudes changing?

I think it’s just a nat­ur­al change and accep­tance curve. When util­i­ties first moved from paper to SAP, trust was still in that paper. When you imple­ment tech­nol­o­gy sys­tems, how do you know the sys­tem has it if you can’t see it? You gain con­fi­dence over time because you use, improve, and con­tin­u­ous­ly gain new learn­ings that increase reli­a­bil­i­ty and con­fi­dence. This builds trust. AI will also fol­low this curve.

Let me share an inter­est­ing sto­ry about the solu­tion I men­tioned ear­li­er, Cognizant’s Case Man­age­ment AI Agent for SAP solu­tion. The Cog­nizant team devel­op­ing this solu­tion had cut­ting-edge AI tech­ni­cal team mem­bers to address those to build the solu­tion, but more impor­tant­ly we had a vet­er­an util­i­ty billing expert who is one of the lead­ing rec­og­nized SAP billing experts in the indus­try. Even she had her doubts about whether AI could deliv­er! Now she is the biggest advo­cate for the AI solu­tion, know­ing how this would have sim­pli­fied her util­i­ty job in the past. She also has incred­i­ble con­fi­dence in this solu­tion because secu­ri­ty and pri­va­cy were also addressed and con­firmed in the devel­op­ment process and testing.

Con­nect with Gary Hayes on LinkedIn.

So, yes, atti­tudes are chang­ing. Suc­cess­es like Case Man­age­ment high­light why it’s the right time to embrace the ben­e­fits of AI across end-to-end work­flows. Start with quick wins, then build momen­tum toward tack­ling more com­plex dig­i­tal trans­for­ma­tion oppor­tu­ni­ties. Trust is earned one suc­cess at a time.

Q: Which AI or automa­tion use cas­es are prov­ing most impact­ful right now in utilities? 

Com­bin­ing AI and automa­tion is prov­ing the most impact­ful right now. AI-dri­ven automa­tion use cas­es are the most preva­lent because they are fit for pur­pose. They have tar­get­ed actions to take, giv­en spe­cif­ic para­me­ters. AI is increas­ing­ly sup­port­ing com­plex, fit-for-pur­pose needs. Areas in engi­neer­ing, grid oper­a­tions, cus­tomer ser­vices, and finan­cials are oth­er examples.

The fol­low­ing are some oth­er notable areas/​examples: AI and automa­tion solu­tions tar­get cus­tomer and employ­ee ser­vices (AI-pow­ered chat­bots), grid man­age­ment and oper­a­tions (AI capa­bil­i­ties aug­ment­ing engi­neer­ing and sys­tem oper­a­tions), cyber­se­cu­ri­ty (AI capa­bil­i­ties mon­i­tor­ing and pro­tect­ing), finan­cial and reg­u­la­to­ry (AI capa­bil­i­ties sup­port­ing major invest­ment deci­sions and/​or reg­u­la­to­ry work­load man­age­ment). As not­ed, these are very tar­get­ed solu­tions address­ing com­plex, but spe­cif­ic, needs.

We have been dis­cussing sev­er­al spe­cif­ic use cas­es that are Agen­tic AI. Agen­tic AI can break down the silos and make the data avail­able across the enter­prise, which will fun­da­men­tal­ly shift the way the process­es are defined and oper­at­ed today. The Case Man­age­ment solu­tion is Agen­tic AI. It dif­fers from tra­di­tion­al AI because it can inde­pen­dent­ly lever­age enter­prise solu­tions, inter­pret data, and adapt strategies/​approaches to achieve tar­get­ed objectives.

Q: With decades of bolt-ons, workarounds, and cus­tom code, how do you approach sim­pli­fied inte­gra­tion, and what role does AI play in ratio­nal­iz­ing that complexity?

We are con­tin­u­ing to see orga­ni­za­tions tar­get­ing a Brown­field migra­tion with spe­cif­ic improve­ment out­comes and deliv­er clean-core solu­tions with­in the scope. Also, many of those out­comes are focused on tar­get­ed SAP improve­ments and align­ing lega­cy inte­gra­tion to sup­port the trans­formed S/4HANA environment.

Anoth­er essen­tial com­po­nent of your ​“mag­ic” foun­da­tion for your ​“Util­i­ty of the Future” is a clean core. When you sim­pli­fy your archi­tec­ture and oper­a­tions, you can be more agile and effi­cient. Real­ly, regard­less of where you are on the scale from Brown­field to Green­field, your objec­tive is to achieve a clean core with your final SAP S/4HANA solu­tion. It’s impor­tant to be aware that even with a Green­field start­ing point, you will like­ly find chal­lenges relat­ed to the lega­cy inte­gra­tion lay­ers per­haps hold­ing you hostage to your his­to­ry of customization.

This is why your ini­tial trans­for­ma­tion analy­sis and plan­ning, typ­i­cal­ly referred to as Phase 0, are crit­i­cal­ly impor­tant. Regard­less of where you are on the spec­trum from Brown­field to Green­field, what is your planned sequence of deliv­ery over­time? As we dis­cussed, we have seen most trans­for­ma­tion projects, at this point, result in a Brown­field approach that address­es crit­i­cal process­es now and ben­e­fit­ing the orga­ni­za­tion by mov­ing to the S/4HANA foot­print — the foun­da­tion for future improve­ments. A vari­a­tion from this is Brown­field with changes to move to new SAP fea­tures and solu­tions, such as Sales and Ser­vice Cloud V2 or Field Ser­vice Man­age­ment. These vari­a­tions iden­ti­fied in Phase 0 dri­ve approach­es around the inte­gra­tion between these solu­tions and oth­er oper­a­tional or cus­tomer sys­tems. The required objec­tive remains the same: stay true to the clean-core prin­ci­ples. This sequence of tran­si­tion­al trans­for­ma­tions must be plan­ful. In oth­er words, plan the path­way and step­ping stones to your end-state objec­tives. The key word is ​“plan­ful” because this ear­ly design plan­ning estab­lish­es the foun­da­tion for the clean core, and the future step­ping stones are the clean path for the sub­se­quent transformations.

Cog­nizant and its SAP trans­for­ma­tion part­ners, such as Natu­vion, have devel­oped AI solu­tions to address the com­plex­i­ties of reme­di­a­tion as well as the prepa­ra­tion and trans­for­ma­tion of the data. Devel­op­ment of code could lever­age AI and automa­tion to facil­i­tate short­er devel­op­ment times and test­ing. Lever­ag­ing tools like SAP WalkMe pro­vides not only a plat­form for learn­ing, but a plat­form for per­sona inter­ac­tion (employ­ee or cus­tomer) dri­ven by AI to meet the needs of the per­sona. Agen­tic AI solu­tions, such as Cognizant’s Case Man­age­ment, are incor­po­rat­ed into the process­es to facil­i­tate increased pro­duc­tiv­i­ty and cus­tomer satisfaction.

Q: From a change man­age­ment per­spec­tive, have strate­gies evolved, or are they large­ly the same ideas applied to a new realm?

Strate­gies have and will con­tin­ue to evolve as each gen­er­a­tion of user com­mu­ni­ties emerges. Each gen­er­a­tion of dig­i­tal natives will have expec­ta­tions or accep­tance relat­ed to AI, and more impor­tant­ly an expec­ta­tion that it is there to assist them in the per­for­mance of their work. The need for new strate­gies and approach­es is greater today. That move from paper to tech­nol­o­gy was a giant step. Just think about these next steps.

We are also in this world where there’s stronger exter­nal moti­va­tion com­ing from cus­tomers, sup­pli­ers, and new reg­u­la­tors around this dig­i­tal foot­print. It’s an expec­ta­tion. And from that stand­point, the next-gen­er­a­tion work­force will make the deci­sion whether they’re going to work for you or not.

Vis­it the Cog­nizant web­site. 

When you engage and lever­age change man­age­ment, you cre­ate expec­ta­tions. If you over­sell, you’re going to under-deliv­er almost imme­di­ate­ly. Make sure peo­ple under­stand why you’re mak­ing the changes, how the changes will impact the com­pa­ny and them per­son­al­ly, and then enable them through tech­nol­o­gy, edu­ca­tion, and own­er­ship. As men­tioned before, dig­i­tal enablers like WalkMe are great exam­ples. If they don’t know how to accom­plish some­thing using the new tech­nol­o­gy, they can get the answer. They don’t have to wait. I think expec­ta­tion man­age­ment is going to be a greater chal­lenge in this trans­for­ma­tion. The time, speed, and desire to deliv­er the capa­bil­i­ties we have dis­cussed will also have change-man­age­ment implications.

Q: How can orga­ni­za­tions bal­ance AI-dri­ven inno­va­tion with the cyber­se­cu­ri­ty and reg­u­la­to­ry rig­or that crit­i­cal infra­struc­ture demands?

As a util­i­ty, you may not typ­i­cal­ly be an expert in all com­pe­ten­cies. You are, how­ev­er, an expert in your space. You put a lot of trust and reliance on your part­ners. SAP, by design, pro­tects the SAP sys­tem from exter­nal threats. You will lever­age SAP and oth­er cyber­se­cu­ri­ty pro­tec­tion solu­tions much as you do today. Many of these cyber­se­cu­ri­ty solu­tions are on a par­al­lel path to AI inno­va­tion. The devel­op­ment of inter­nal AI capa­bil­i­ties will pro­gres­sive­ly mature. What util­i­ties should focus on first is bring­ing the knowl­edge and rig­or of trans­lat­ing reg­u­la­to­ry, crit­i­cal infra­struc­ture, and oth­er util­i­ty-rel­e­vant cyber­se­cu­ri­ty and crit­i­cal infra­struc­ture require­ments to the fore­front of these emerg­ing solutions.

Ear­ly, you’re rely­ing on your providers. You are and must be involved with SAP as the trans­for­ma­tion con­tin­ues. You need to be par­tic­i­pat­ing in orga­ni­za­tions, like ASUG, hav­ing dia­logue about inno­vat­ing while imple­ment­ing and/​or main­tain­ing improve­ments to pro­tect data, secu­ri­ty, and sys­tem integrity.

In clos­ing, Cog­nizant can help. We are work­ing with sev­er­al util­i­ties right now to imple­ment AI solu­tions for a vari­ety of val­ue-based use cas­es, from the back office to cus­tomer ser­vice to field oper­a­tions and oth­ers that sup­port the trans­for­ma­tion­al demands they face.

As util­i­ties plan for and imple­ment these next-gen­er­a­tion dig­i­tal and intel­li­gent sys­tems, as well as the dig­i­tal trans­for­ma­tion­al changes that go along with them, they can be con­fi­dent that the jour­ney is worth­while and achiev­able. And with a lit­tle ​“mag­ic” they’ll become that util­i­ty of the future.