Field notes from the rooms where enterprise AI gets decidedNext room: Singapore & New York · 13 Nov 2026
CIO Vision

Leadership priorities

Data platforms: what enterprise AI leaders are working on

28%

of 731 themed leaders · 205 leaders

AI strategy
59%
Digital transformation
53%
Operational efficiency
48%
Analytics & decisions
38%
Talent & culture
37%
Growth & partnerships
31%
Data platforms
28%
Data governance
26%
Customer experience
21%
Share of 731 themed leaders, by theme

Source: 731 CIO Vision leader profiles with at least one priority theme, from 739 leaders in the series. Leaders can be counted in more than one theme.

Leaders building the data and cloud foundations that analytics and AI depend on. The work covers architecture, data engineering, integration and modern data stacks.

AIM ResearchCIO AI Priorities 2027

The real work sits underneath the agents

Data foundations take 28% of AI hiring and only 14% of what CIOs say in public.

Read the finding
28%of AI hiring
14%of what CIOs say
249data foundation buyers in the cohort
Index score4.7 of 12 · rank 2 of 10

Leaders working on Data platforms

All 205 leaders
Alaa MoussawiAnil PrasadAnubha GaurDavid LowDeepti SinghDr Knarig ArabshianEJ KimGopichand MannavaJohn AngLee SarkinManish KumarMarcel MeyerMichael ShawNirmal JingarRohan ChopraSanthosh MahendiranSpriha G.Xin JinAngelo ClaytonRobert WilsonTahira ShaheenAaron JonesDaniel LiEsther WuVincent KwanBinu VargheseGaurav SingalJatinear GivensPankaj SingalSatya A.Varun TottempudiAntonius HermawanDr. Irvan Bastian AriefErwin SusiloHerman WidjajaIhsan FauziKukuh T WicaksonoMohammed AlabsiPoetri HeriningtyasRestu KresnadiVaruna De Wass GunawardAddhyan PandeyAkansha SaxenaAnn BhattacharyaBijan VafaeiDessa GypaloGunjan KheraLily LiMichelangelo D' AgostinoRaju DebroyRamon BaezShuen MeiSusan JacobVijay RajandramVishal PandyaAdrien WartelAkihiko KawanoFidens SimanjuntakFigen UlgenHitoshi NakayamaJumpei OkamotoKenji HiramotoKohei NishidaKunal KushwahaManzur MahtabMasaru HashimotoMasayuki KuboMatsutani AdelaRasool AghdamTaiki FukunagaAlex ChiAlex CK YapDatin Dr. Ts. Habsah NordinDr. Muhsin HassanDr. Sadesh ManikamHong H. OngIffah Illani IsmailIja MohanKong Siong LinMilan DhingraTristan EljedTs. Edwin Chong Kok HuiJacqui NevilsJaya GwalaniMeghna TrivediRaghu KolathRajesh RamaswamyVictor DavidsonVikas SachdevaAbhinav MangalDejan JovanovGaurav JindalJoshua OnffroyManoj HemanthNamo TiwariPrasanth PalaRajit SahaRamin MobasseriSamiksha GourSiwei ShenSumesh KumarArun ShastryKaren NogueiraKarthikeyan IlangovanKrishna Kishore GajjalaMike TurnerMohan MenonRajitha MunugalaSandeep AhluwaliaTania MartinezTy EastVeeru RamaswamyVino KingstonAshleigh BynumBryan NadenDavid HeNaqi KhanNirmala SistlaRohit DudaniSuresh PunnaVenkat SurapaneniBrijesh PandyaHonglin ZhangAndré Michel VargasEric KimGoutham BudatiHovannes DanielsJamil BadrudeenMumtaz VauhkonenTosin AlabiAdam FreemanAltaf PatelAyo BabajideBini YoheswaranDayanidhi M AadaliGerald SchmidtManoj TripathiMasood AlamNeil ThewlisSukant PandeyAmine MansourKartik IyerNithesh PejavarOmar AboutalebPrakash LogaiyaRishi JainRizwan TufailSandeep SrivastavaVictor AdewusiMikhail LisovichRahul LathStanislav RosenbergSundari VeerabahuAdris MisraAndrew BeierAndrew DouglasAnkur JainArun VermaArvind RajagopalanAshish MishraAshok JakatiBadrinath PanyamBijit GhoshBiswajit MahapatraDevendra Singh ParmarDivya PrakashDouglas ElfersDr. Ahmad HaiderEsra KasapogluFrançois MillardGreg ManarisIsaac KamaleshIsmail Khan MohammedJason MestritsJeff XiaJyoti MishraKarthik ChallaMajoni MaumbeMan Chon (Kevin)Mansoor (Mohammad) PanawalaMarcos AcostaMichael DownMohammad Farhan AlamNaveen KolliOliver GomesPooja DewanPrince PaulrajRajeev KapurRajkumar BondugulaRani SinnasamyRavindra HarveRooshana PurnynSayeed ShariffScott NewtonSpriha GogiaSrinivas AkellaSudipto GhoseSven HansenTim RiddleUnais T.Vipan GuptaWade MossWaseem Akram SyedXi LiangAndrea Farris

Conversations in the room

Panel Discussion: Modernizing the Foundation - Why Your AI Ambitions Live or Die on Data & Infrastructure

AI ambitions rarely come with a blank cheque. As budgets tighten and finance scrutinises every rupee, tech leaders are under pressure to keep innovating while spending smarter. This panel explores how enterprises are funding their AI bets in a constrained environment, reallocating spend, sunsetting low-value projects, and building the business case for investment when every line item is questioned. The discussion will offer real strategies for stretching resources, prioritising ruthlessly, and proving returns without waiting for the perfect budget.

Panel Discussion: Doing More With Less: Driving Innovation Under Tighter Budgets

Every ambitious AI roadmap eventually collides with an unglamorous truth: models are only as good as the data and infrastructure beneath them. This panel brings together enterprise tech leaders to talk candidly about the foundational work that determines whether AI initiatives scale or stall, cleaning up fragmented data, modernising legacy systems, and paying down technical debt, all while continuing to ship. Expect a practical conversation on where to invest first, how to fix the plumbing without halting progress, and why the least visible work often decides who wins with AI.

Panel Discussion: Agentic AI and the Future of Enterprise Growth

The future of enterprise growth is closely tied to the adoption of agentic AI, which offers capabilities far beyond traditional AI by enabling autonomous execution. This panel will examine how agentic AI enables continuous improvement in business processes, drives competitive differentiation through faster innovation cycles, and supports customer experiences. Leaders will discuss how to build resilient enterprise architectures that fully leverage agentic AI’s potential. They will also explore strategies for aligning AI initiatives with organizational goals, addressing ethical and governance considerations, and preparing the workforce for AI-driven transformation.

The Vision Talk: AI Transformation - New Ways Of Working

The next phase moves AI beyond pilots into how the enterprise actually runs. Priorities follow business value and ROI, starting with supply chain, customer service, order entry, and software development. A dedicated enablement team drives delivery on a foundation of disciplined buy-versus-build decisions, a secure platform and AI-ready data products. Tiers of training builds an AI-first culture, while live governance policies keep adoption responsible and fast.

Panel Discussion: Agentic AI and the Future of Enterprise Growth [パネルディスカッション：エージェンティックAIとエンタープライズ成長の未来]

The future of enterprise growth is closely tied to the adoption of agentic AI, which offers capabilities far beyond traditional AI by enabling autonomous execution. This panel will examine how agentic AI enables continuous improvement in business processes, drives competitive differentiation through faster innovation cycles, and supports customer experiences. Leaders will discuss how to build resilient enterprise architectures that fully leverage agentic AI’s potential. They will also explore strategies for aligning AI initiatives with organizational goals, addressing ethical and governance considerations, and preparing the workforce for AI-driven transformation. [エンタープライズの成長の未来は、自律的な実行を可能にするエージェンティックAIの導入と密接に結びついています。このパネルでは、エージェンティックAIがビジネスプロセスの継続的な改善をどのように実現し、より速いイノベーションサイクルを通じて競争上の差別化を促進し、顧客体験を支えるかを検討します。リーダーたちは、エージェンティックAIのポテンシャルを最大限に活用するための強靭なエンタープライズアーキテクチャの構築方法について議論します。また、AIイニシアティブを組織目標と整合させ、倫理・ガバナンス上の課題に対応し、AI主導の変革に向けて人材を準備するための戦略についても考察します。]

Open Roundtable: Building the AI Native Organization

Becoming an AI-native organisation isn't just about adopting new technology; it's a transformation spanning people, data, and strategy. It starts with culture: shifting AI from a specialist tool to an embedded capability that augments every role. Even with the right mindset, AI is only as powerful as the data beneath it. The real value often lies hidden in the connections between data silos, not within them. Organisations that uncover and reason across these relationships unlock insights that flat, siloed data cannot reveal. Get culture and connected data right, and competitive advantage follows.This roundtable explores the journey from AI adoption to AI-native, examining the cultural shifts required, the data architectures that enable it, and how organisations that master both will outpace the competition.

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Open Roundtable : Building the AI Native Organization

Becoming an AI-native organisation isn't just about adopting new technology; it's a transformation spanning people, data, and strategy. It starts with culture: shifting AI from a specialist tool to an embedded capability that augments every role. Even with the right mindset, AI is only as powerful as the data beneath it. The real value often lies hidden in the connections between data silos, not within them. Organisations that uncover and reason across these relationships unlock insights that flat, siloed data cannot reveal. Get culture and connected data right, and competitive advantage follows. This roundtable explores the journey from AI adoption to AI-native, examining the cultural shifts required, the data architectures that enable it, and how organisations that master both will outpace the competition.

Vision Talk: From AI Strategy to AI-Native Execution:

The evolution of the data and AI leader’s scope - from data warehousing and BI to generative and agentic AI - and why this shift fundamentally changes expectations of impact and accountability. How governments can deliver a quantum leap in citizen experience by moving beyond bolted-on AI toward truly AI-native platforms, and the realities of doing this at scale in a regulated environment. Key lessons from execution: building AI talent at scale, resisting technology hype cycles, and anchoring AI transformation in outcomes, trust, and disciplined operating models.

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