The expe ie ces a e pa t of Livi g Secu ity’s gamified Cybe secu ity Awa e ess Mo th offe i g, which gives secu ity awa e ess teams the speake s, i te active expe ie ces, campaig co te t, employee commu icatio s, pla i g esou ces, a d suppo t eeded to u a e gagi g Octobe p og am.
As a tificial i tellige ce t a sfo ms the th eat la dscape, employees a e i c easi gly co f o ted with commu icatio s a d ide tities that appea legitimate but may be e ti ely fab icated. Deepfake videos, voice clo i g, AI-ge e ated phishi g, a d automated social e gi ee i g attacks a e maki g deceptio mo e co vi ci g a d t aditio al wa i g sig s less eliable.
Built a ou d Livi g Secu ity’s 2026 Cybe secu ity Awa e ess Mo th theme, Navigati g T ust i a AI Wo ld, the ew expe ie ces help employees p actice o e of the most impo ta t secu ity behavio s of the AI e a: k owi g whe to pause a d ve ify befo e taki g actio .
“Tech ology is cha gi g apidly, but o e p i ciple emai s co sta t: ve ify befo e you t ust,” said Ashley Rose, CEO a d Co-Fou de of Livi g Secu ity. “These expe ie ces give employees ha ds-o oppo tu ities to ecog ize deceptio , questio assumptio s, a d p actice the behavio s that educe huma isk.”
Ac oss th ee i te active ou ds, pa ticipa ts evaluate sce a ios i volvi g deepfake video, clo ed voices, phishi g, smishi g, impe so atio attacks, a d AI-powe ed automatio . Audie ces pa ticipate collectively, ide tifyi g suspicious situatio s a d decidi g whe i fo matio o ide tities should be ve ified befo e actio is take .
Rathe tha teachi g employees to ely o visual glitches, poo g amma , obotic voices, o othe tech ical clues that a e becomi g less depe dable as AI imp oves, Ve ified focuses o co textual wa i g sig s such as u expected u ge cy, cha ges to o mal p ocesses, u familia commu icatio cha els, a d u usual equests fo mo ey, c ede tials, o se sitive i fo matio .
The expe ie ce also i t oduces eme gi g isks, i cludi g p ompt i jectio a d AI age ts acti g o suspicious i fo matio , ei fo ci g that automatio does ot eplace the eed fo huma judgme t a d ve ificatio .
Pa ticipa ts i vestigate how a sophisticated f aud attempt ea ly esulted i fi a cial loss
The expe ie ce demo st ates how attacke s ca build ealistic scams without fi st b eachi g a o ga izatio ‘s systems, usi g i fo matio f om compa y a ou ceme ts, p ofessio al p ofiles, ve do elatio ships, a d othe public sou ces to make f audule t commu icatio s appea c edible.
Th oughout the i vestigatio , pa ticipa ts p actice th ee c itical behavio s:
- Slow dow befo e acti g
- Ve ify i fo matio a d ide tities th ough a t usted cha el
- T ust evide ce a d established p ocesses, ot assumptio s
The expe ie ce ei fo ces that as attacks become mo e tech ologically sophisticated, simple huma behavio s, such as i depe de tly ve ifyi g a u expected equest, emai powe ful defe ses.
Ve ified a d T ust No O e place employees i ealistic situatio s whe e they must evaluate i fo matio , make decisio s, a d p actice secu e behavio s athe tha simply co sume awa e ess co te t.
They a e two compo e ts of Livi g Secu ity’s b oade
Livi g Secu ity’s 2026 State of Huma Risk Repo t fou d that 74.8% of isky behavio t aces to the iskiest 10% of the wo kfo ce, yet two i th ee people i this yea ‘s iskiest 10% we e ot o last yea ‘s list. The fi di gs show that huma isk is co ce t ated but co sta tly cha gi g, ei fo ci g the eed to e gage employees a d ma age isk co ti uously th oughout the yea .
Togethe , these esou ces help o ga izatio s tu Cybe secu ity Awa e ess Mo th e gageme t i to behavio s that suppo t a b oade Huma Risk Ma ageme t st ategy a d measu able isk eductio th oughout the yea .
Ve ified a d T ust No O e a e available as pa t of Livi g Secu ity’s 2026 Cybe secu ity Awa e ess Mo th p og am.
O ga izatio s ca explo e the complete p og am, i cludi g speake s, i te active expe ie ces, campaig co te t, commu icatio s esou ces, a d pla i g suppo t, at
Livi g Secu ity is the global leade i Huma Risk Ma ageme t, helpi g o ga izatio s ide tify, measu e, a d educe huma cybe isk ac oss huma s a d AI age ts. Its AI- ative Huma Risk Ma ageme t platfo m combi es behavio al, ide tity, a d th eat i tellige ce to p edict isk, guide espo se, a d p eve t cybe i cide ts befo e they occu . By co ecti g secu ity data to measu able busi ess outcomes, Livi g Secu ity e ables o ga izatio s to co ti uously educe wo kfo ce isk while st e gthe i g o ga izatio al esilie ce.
