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    • Home
    • THE AI-FIRST CEO/ CXO
      • Why AI must be CEO-led?
      • GenAI CoE Org Structure
      • CEOs Choose Right AISPs
      • SPs of AI-Powered CEOs
    • Platform Engineering: How
      • How to Win on Platforms?
      • Greenprinting Platforms
      • Platformizing Businesses
      • What's your Platform?
      • Top10 Platform Engg Steps
    • What's AI Storytelling?
      • Gesalt's Principles in AI
      • AI-Cloud Change Pilot: U
      • What's your AI story?
      • 5 C's of AI-Data-Cloud
      • Unique AI stories: How to
      • Checklist: AI Narrative
      • AI Storytelling with 5D's
    • 3-Mnt Story Boilerplates
      • AWS: Cloud-AI-Data Pivots
      • Why U must build AI story
      • How to build 3-mnt story
      • AI Boilerplate Example
      • Output: A 3-Mnt AI Story
      • Declutter AI: Power of 3
    • What's Data Storytelling
      • 5 Datastory Techniques
      • Date Story Technologies
      • Top 5 Data Story Tools
      • 3-Minute Data Stories
      • SO-WHAT Story Technique
      • Datastory QnA Boilerplate
    • AI PRACTICE TOOLS- SWITCH
      • AI PRACTICE- END USER
      • AI PRACTICE- TSP
      • FAQ- AISWITCH USAGE
    • PRACTICE-RESEARCH BLOGS
      • ALL RESEARCH BLOGS
      • STATE OF LANGUAGE AI
      • CUSTOMER-INSPIRED AI- AWS
      • THE BIGGEST Q- AI ETHICS
      • TSP, ITSP, INDUSTRY BLOGS
    • Selling AI Right
      • Why Value-Sell AI
      • 5 Cs of ValueSelling AI
    • Why AISWITCH
    • WHAT WE DO
    • WHO WE ARE
  • Home
  • THE AI-FIRST CEO/ CXO
    • Why AI must be CEO-led?
    • GenAI CoE Org Structure
    • CEOs Choose Right AISPs
    • SPs of AI-Powered CEOs
  • Platform Engineering: How
    • How to Win on Platforms?
    • Greenprinting Platforms
    • Platformizing Businesses
    • What's your Platform?
    • Top10 Platform Engg Steps
  • What's AI Storytelling?
    • Gesalt's Principles in AI
    • AI-Cloud Change Pilot: U
    • What's your AI story?
    • 5 C's of AI-Data-Cloud
    • Unique AI stories: How to
    • Checklist: AI Narrative
    • AI Storytelling with 5D's
  • 3-Mnt Story Boilerplates
    • AWS: Cloud-AI-Data Pivots
    • Why U must build AI story
    • How to build 3-mnt story
    • AI Boilerplate Example
    • Output: A 3-Mnt AI Story
    • Declutter AI: Power of 3
  • What's Data Storytelling
    • 5 Datastory Techniques
    • Date Story Technologies
    • Top 5 Data Story Tools
    • 3-Minute Data Stories
    • SO-WHAT Story Technique
    • Datastory QnA Boilerplate
  • AI PRACTICE TOOLS- SWITCH
    • AI PRACTICE- END USER
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    • STATE OF LANGUAGE AI
    • CUSTOMER-INSPIRED AI- AWS
    • THE BIGGEST Q- AI ETHICS
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  • Selling AI Right
    • Why Value-Sell AI
    • 5 Cs of ValueSelling AI
  • Why AISWITCH
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Right SPs for Right AI-Powered CEO

How can the SPs become CEO's Real Value Partners?

SPs must elevate their vision in line with their strategic client CEOs' vision and mandates, for real AI-data-cloud value realizations to be seen at the client enterprises: 



Focus on client business impact measurements: Best practices for SPs should be embedded in cloud strategies, e.g. clients' business interlock-based storyboards at KPI levels. For all service providers' AWS GCP MS.sales and marketing strategies, their target client leadership/ buying center persona-based themes can be based on clients' business big bets mapping, e.g. :

  • Clients' BU heads + CTOs combined Big Bets: For high-impact strategic AI/ GenAI usecases e.g. organization-wide usage of Copilots for all enterprise knowledge search, document intelligence, automated form-filling, HR and employee related, and other horizontal usecases e.g. on legal, risk and compliance, governance and regulatory reporting and liabilities monitoring
  • Customers and Client partners Domain SMEs combined Big Bets- e.g. for at least 50:50 outcomes-based contracts so that at least 50% of the CV includes the ITSP/ CSP partners' skin-in-the-game. This strategy can work best for functional/ domain specialist AI usecases, e.g. insurance claim fraud detection, security threat predictions, retail leakage prediction, telco's customer churn and ARPU predictions, financial portfolio yield predictions etc.
  • CTO’s and CSP/ SI/ SP Tech Partners being jointly accountable: For example, with MS in multiple areas involving Copilot, GCP for 20+ vertical areas combining multiple models across vertex and Gemini, and 80-90 functional areas. Solutions and POCs around these hyperscaler partner and client ecosystems, can include multi-model specialist high-security usecases e.g. healthcare diagnostics. 


Develop Integrated AI-Data-Cloud advisory as starting point: Critical to create, build, test, deliver and manage lifecycles of overall platform experience. Platforms with pre-curated industry specific integrative cloud-data-AI models, benchmarkable performance and value/ impact datasets for client organizations by regions-industry-size, differentiated solutioning with mitigated locking for customers. 


Offer at least 3 lenses on Lead Buying Center Personas: 

1- By verticals, 

2- whether IT or innovation or business-led, 

3- by technologies. 


Alternatively, 

1- By verticals, 

2- By Team persona's e.g. CIO-IT or CDO-Digital or CXO/ BU- Business-led, and

3- By technologies e.g. CTO or AI CoE led. 


For a balanced business value-based progression in cloud journeys, all three lenses are important, like 3 swim-lanes in software engineering. Also the consulting-led solutioning (pre-sales) value propositions should be in sync with the core  capabilities for example the Gartner ITScore dimensions of people-process-tech-business. with best practices and maturity levels benchmarked in 360 ways, by verticals (Business value metrics), whether IT or innovation or business-led (People and Process), by technologies (Tech/ tools/ tech partners).



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bandopadhyay@aiswitch.org (Research & Advisory Services)

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  • Gesalt's Principles in AI
  • What's your AI story?
  • Why U must build AI story
  • How to build 3-mnt story
  • Declutter AI: Power of 3
  • 5 Datastory Techniques
  • Top 5 Data Story Tools
  • 3-Minute Data Stories
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