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Prashant Kankokar
Founder and Head - AI Adoption and Change Management @ Neotic AI
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About Prashant Kankokar
Enterprise Transformation & GCC/GBS/GSS Leader | OCM (Prosci), Pre-Sales & Operating Models (TOM) | Enterprise AI Adoption | Process Excellence | $25M Value Realized, 30% Win Rates | Ex-PwC, Ex-Maersk, Ex-Amazon
Over 18+ years at the intersection of commercial deal strategy and operational delivery, I lead Enterprise Transformation, GCC/GBS incubation, and digital modernization across global consultancies, captive centers, and industry leaders (Ex-PwC, Ex-Maersk, Ex-Amazon). My work bridges two critical phases of enterprise change: 1. Shaping & Winning Mandates: Translating complex business challenges into competitive, multi-year transformation proposals and high-win-rate RFP/RFI solutions across BFSI, Manufacturing, Supply Chain, and Healthcare. 2. Delivering Operational Value: Designing Target Operating Models (TOM), cross-border governance, and driving behavioral adoption (Prosci ADKAR) to secure sustainable P&L impact. CORE PRACTICE AREAS • GCC/GBS Leadership & TOM: Setting up, scaling, and stabilizing global capability centers; defining multi-site governance, service catalogs, RACI models, and SLA/KPI frameworks. • Enterprise AI & Governance: Transitioning from pilots to governed operations via multi-LLM architectures, responsible-AI guardrails, and agentic workflows. • Process Excellence & Mining: Applying Lean Six Sigma Black Belt rigor, Celonis process mining, and intelligent automation to eliminate friction and compress cycle times. • Change Management (OCM): Utilizing Prosci ADKAR frameworks, champion networks, and coaching to turn roadmaps into adopted operational behaviors. • Governed investment prioritization and operating model execution across large portfolios, delivering recurring savings, major productivity gains, and enterprise upskilling. • Led global finance Lean Six Sigma initiatives, compressing close timelines, clearing critical operational backlogs, and eliminating process waste. • Unlocked double-digit efficiencies via process mining across millions of events; led Industry 4.0/IoT advisory integrating sensor-to-ERP architectures. • Commercial Leadership: Owned P&L and GTM strategy for identity platforms, consistently exceeding revenue targets. • MBA, University of Sheffield (UK) | Executive Certificate in Product Management, ISB | BSc Computer Science, Pune University • Lean Six Sigma Black Belt | Prosci ADKAR (Trained) | PRINCE2 Practitioner | ICP-ACC Agile Coach Open to conversations with GCC Country Heads, Transformation Practice Leaders, and GBS Executives. Email: [email removed] | Pune, India (Open to Domestic & European Relocation)
B2BAISaaS
My LinkedIn audience
- Followers
- 10,069
- Est. median reach
- 56
- Reactions per post
- 1
- Median of recent posts
Public LinkedIn data · Sep 28, 2026
Recent posts
All posts on LinkedInPrashant Kankokar
Before I let an AI agent change a purchase order in SAP, I want to know who can stop it - and how. Most agent deployments I see cannot answer that. Permissions are binary, monitoring is a quarterly review, and nobody owns the stop button. Four controls I would put in place before production access: 1. Tier the authority. Read, draft, stage, execute. Full execution only with hard transaction caps. Autonomy is calibrated to task criticality, not granted as a package. 2. Constrain the tools. Least-privilege tokens, parameter boundary checks, schema validation on every call. An agent with unconstrained API access is an injection path, not a productivity gain. 3. Detect and contain failures. Monitor actions, spend and repeated calls. Define when execution stops, who gets alerted and how recovery works. Test those controls before release. 4. Name the decision owners. Business, security, legal and engineering need clear responsibilities - not just seats on an AI council. Someone must own approval, exceptions and incident response. These controls will not remove every risk. They make delegated authority explicit and failures easier to contain. That is delivery work, not a governance slide: permissions configured, stop mechanisms tested, owners ready. What evidence would you require before letting an agent execute a production transaction?
13 reactions · 0 commentsViewPrashant Kankokar
Most AI pilots don't fail in the demo. They fail in the weeks after. The pattern I keep seeing with enterprise teams: 1. The pilot proves the tech works, but nobody owns the rollout. 2. Teams get trained on the tool, not on the new way of working. 3. Leadership celebrates the launch, then moves on before adoption sticks. The fix isn't more AI. It's change management: clear ownership, new habits, and leaders who keep showing up after go-live. I've spent 18+ years helping organizations make change stick across PwC, Maersk and Nitor. If you're working through AI adoption, or planning your next career move in this space, I've opened a few 1:1 slots this month - link in the comments. #AIAdoption #ChangeManagement #DigitalTransformation
1 reactions · 1 commentsViewPrashant Kankokar
The team did not resist AI. They were left to carry it. A new tool arrives. The demo looks effortless. Then someone in operations has to check every output, explain every exception and answer the customer when it goes wrong. None of that work was in the ROI slide. Before calling an AI rollout successful, I ask four questions: 1. Who owns the outcome when the model is wrong? 2. What work did we remove, and what new checking work did we create? 3. Can a colleague pause the workflow without being punished for slowing it down? 4. What changed for the customer, not just the internal dashboard? Adoption is not a training attendance figure. It is whether people can do better work with the system and still exercise judgment. If your team is introducing AI and the operating model feels unfinished, I offer a focused AI adoption and transformation strategy call. Start with a free 15-minute intro if you want to test the fit: https://lnkd.in/gnGiXdV6
1 reactions · 0 commentsView
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Based on 21 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.
Based on 21 people who reacted to or commented on my posts. Percentages use the profiles that could be classified.
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Prashant Kankokar is a B2B LinkedIn creator based in India with 10,069 followers, posting about AI and SaaS. On Naano, one sponsored LinkedIn post by Prashant Kankokar costs €188, a fixed price per post. Prashant Kankokar is not taking new bookings right now.
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