How CTOs Can Lead Enterprise AI Transformation

View profile for Sanjeev Vohra

Futurist | Innovator | Technologist | People-first Leader

AI is reshaping enterprises, and it's up to CTOs to lead the transformation. Tomorrow's CTOs will be more than technologists; they also need to be strategists, architects, evangelists and integrators. With the rise of #AgenticAI, successful CTOs must have the vision to challenge norms and rethink fundamentals by:   💡Commanding the shift and becoming an AI evangelist  💡Reimagining the tech stack, from SDLC to ADLC  💡Building AI-centric teams beyond coders  💡Driving ROI by innovating with accountability  💡Securing by design for AI security and governance   Be sure to check out my full piece in InformationWeek here https://lnkd.in/erj2bAEN

Rakesh Verma

Hands-On: Engineering | Solution Architect @ Automation [RPA | GenAI | Agentic AI] | Cloud | DevOps | Python | Golang | Java

3w

Thoughtful post, thanks Sanjeev Vohra

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Ravi Kiran Gullapalli

Founder @ Neuron Edge AI - Product Engineering - AI-IOT-Edge-Robotics-Automation Platforms and Digital Modernization

3w

ADLC is perfect concept 👍

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Deepika Bajaj⚡️

Client-Focused GTM Leader | Driving Revenue Growth | Strategic Partner Enablement | Cloud & SaaS Solutions | AI-Powered Business Impact

3w

Thanks for sharing, Sanjeev Vohra. Insightful.

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Rajesh Ganshani

SVP, Global Sales Leader, Technology & AI | Passionate about transforming businesses and building value-based relationships

3w

I renjoyed reading this. Interesting definition of future CTO.

Deep Banerjee

Senior Data & AI Delivery Director | Transformation Program Director | Product innovator | Data Strategy | Data Management |Data monetization |AI enablement

2w

Thanks for sharing, Sanjeev. If I may add—while CDAOs are primarily accountable for driving value from data assets and overseeing the broader data ecosystem, in my experience, CTOs often hold shared or dotted-line responsibility for areas like end-of-life data management, archiving, data quality, lifecycle capabilities, and systematic data value realization.   With AI, for sure the way to enable Data Quality has changed from primitive ways of traditional DQ Tools providing mere insights on count of errors, to AI based self healing DQ constantly checking for anomalies, inconsistencies, or duplicate records and triggers rapid 'auto cleansing' or smart imputation before sending alerts (at least that's what we are doing for Genpact's Clients using our Agentic Data Control Center).   Continuous Data ROI assessment is a key topic—AI-driven analytics now tracks usage, value contribution, and business impact of 'data assets' in real time, enabling CTOs or CDAOs to phase out low-value initiatives or assets and prioritise ones with high impact.

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Saket Kishore

Principal Data Science - Artificial Intelligence | Machine Learning, Generative AI, LLM,Agentic AI | Architect |AI Strategy & Digital

3w

Thanks for sharing insights , Sanjeev!

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