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    • DATASTORY QA BOILERPLATE?
  • WHAT'S AI STORYTELLING?
    • CLOUD-AI: CHANGE PILOT?
    • HOW TO WIN ON PLATFORMS?
    • WHAT'S YOUR AI STORY?
    • 5 C's OF AI-DATA STORIES?
    • BUILD UNIQUE AI STORIES?
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  • 3-MNT STORY BOILERPLATES
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    • WHY BUILD 3-MNT AI STORY?
    • HOW TO BUILD 3-MNT STORY
    • A BOILERPLATE EXAMPLE
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  • Why AISWITCH
  • WHAT WE DO
  • WHO WE ARE
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    • Home
    • WHAT'S DATA STORYTELLING?
      • 5 DATASTORY TECHNIQUES?
      • DATA STORYBOARDING TECH?
      • TOP 5 DATA STORY TOOLS?
      • 3-MINUTE DATA STORIES?
      • SO-WHAT STORY-BUILDING?
      • DATASTORY QA BOILERPLATE?
    • WHAT'S AI STORYTELLING?
      • CLOUD-AI: CHANGE PILOT?
      • HOW TO WIN ON PLATFORMS?
      • WHAT'S YOUR AI STORY?
      • 5 C's OF AI-DATA STORIES?
      • BUILD UNIQUE AI STORIES?
      • CHECKLIST- GOOD AI STORY?
      • 5 D'S- AI STORY-GUIDE?
    • 3-MNT STORY BOILERPLATES
      • AWS CLOUD-AI-DATA LEVERS
      • WHY BUILD 3-MNT AI STORY?
      • HOW TO BUILD 3-MNT STORY
      • A BOILERPLATE EXAMPLE
      • OUTPUT - A 3-MNT AI STORY
      • POWER OF 3: DECLUTTER AI?
    • PRACTICE-RESEARCH BLOGS
      • ALL RESEARCH BLOGS
      • STATE OF LANGUAGE AI
      • CUSTOMER-INSPIRED AI- AWS
      • THE BIGGEST Q- AI ETHICS
      • TSP, ITSP, INDUSTRY BLOGS
    • AI PRACTICE TOOLS- SWITCH
      • AI PRACTICE- END USER
      • AI PRACTICE- TSP
      • FAQ- AISWITCH USAGE
    • Why AISWITCH
    • WHAT WE DO
    • WHO WE ARE
  • Home
  • WHAT'S DATA STORYTELLING?
  • WHAT'S AI STORYTELLING?
  • 3-MNT STORY BOILERPLATES
  • PRACTICE-RESEARCH BLOGS
  • AI PRACTICE TOOLS- SWITCH
  • Why AISWITCH
  • WHAT WE DO
  • WHO WE ARE

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First-ever, AI PRACTICE RESEARCH Think-tank & Patented Frameworks

First-ever, AI PRACTICE RESEARCH Think-tank & Patented FrameworksFirst-ever, AI PRACTICE RESEARCH Think-tank & Patented FrameworksFirst-ever, AI PRACTICE RESEARCH Think-tank & Patented Frameworks
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First-ever, AI PRACTICE RESEARCH Think-tank & Patented Frameworks

First-ever, AI PRACTICE RESEARCH Think-tank & Patented FrameworksFirst-ever, AI PRACTICE RESEARCH Think-tank & Patented FrameworksFirst-ever, AI PRACTICE RESEARCH Think-tank & Patented Frameworks
Contact Us

AISWITCH: Cogito, ergo sum- Build/ lead AI-Cloud Practice?

AISWITCH is a First Mover AI-IA Practice Research Firm that helps global TSPs & end-user companies SELECT, BUILD, RUN ENTERPRISE AI-SWITCH: AI Strategy, Workforce, Information/data, Technology-stacks, Culture & Human-AI Metrics.


MAKE AI DELIVER MEASURABLE RESULTS: 5+ Patented systems, boilerplates, benchmarks.

AI-Automation architecture, frameworks, business case, RoI, metrics research

Why do we matter?- 10K+ research views

VISIBILITY: 10K+ research views in <2 days

Carrying the classic research legacy of actionable, grounded, evidence-based guidance, we @AISWITCH know exactly what challenges the end-user leaders are facing in their AI-automation-data-cloud journeys, and how the TSP's are trying to deliver to net new demands, to stay relevant.

We are the AI & data practices bridge between end-user leaders and their TSP partners, to build impactful & winning AI success stories:

https://in-resources.awscloud.com/the-art-science-of-ai-storytelling




10+ consulting/ advisory engagements, 8+ large research projects delivered < 1 yr

Jeffrey Archer makes a statement for William Warwick, on ABC of governance: "Accept nothing. Believe no one. Challenge everything". The exact same ABCs work in data-AI governance, for limited AI-leveraged organizations creating invisible "code ceilings". 

We are helping top global TSP & EU clients to AI-SWITCH their zero-sum games, into winning moves, working as AI Practice Partners.


I think, therefore I am

Why does AI fail?

AISWITCH- Tamaso ma Jyotirgamaya

AISWITCH- Tamaso ma Jyotirgamaya

THINKING BEFORE YOU LEAP?

Cogito, ergo sum- I think, therefore I am: Rephrasing René Descartes statement on cognition, in today's AIDX (AI-Defined Everything) world:

=> Ego sum doctrina, ergo sum: I learn, therefore I am

=> Honor autem machinae: Machines think, therefore they are

AI-automation Market Predicts:

  1. 73 million jobs are to be automated by 2030 (McKinsey)
  2. AI to create 500K jobs by 2020, 2 million by 2025 (Gartner)
  3. Annual AI-tech startups- $26.6 Bn- 2019, $4.2 Bn- 2014 


READY FOR THE SWITCH 2022 ON?

  • 90%+ organizations are STILL struggling to move AI from POCs to production.  
  • ~73% organizations are doing some AI use-cases in pockets but  still NO CLEAR ORGANIZATIONAL AI STRATEGY, NO OVERALL AI COE available for leverage 
  • Gartner says in 2020 AI hype cycle- AI governance is fast emerging as top priority, given the costs & risks. 

SERVICES

AISWITCH- Tamaso ma Jyotirgamaya

AISWITCH- Tamaso ma Jyotirgamaya

AISWITCH- Tamaso ma Jyotirgamaya

SWITCH from Tamas- Dark (data), to Jyoti- Enlightened (intelligence)


The real AI Death Valley spreads across the tall mountains of dark data & AI-automation tech on the supply-side, and unsurmountable demand-side challenges of scale, adoption, trust & acceptability. 


In a 2020 survey, 92% enterprise leaders said - Board-level governance is an absolute must for AI. 75% said their top priority was to implement global best-practice frameworks. 


AISWITCH fills these gaps, with:

- AI-automation focussed practice evidence-based research

- Patented, ITIL-like frameworks, to manage 6 key dimensions, in AISWITCH (IP): AI Strategy, Workforce, Information (data), Technology, Culture, Human-AI metrics.

AISWITCH ensures Purposeful-Impactful-Mindful Metrics-driven AI that is strategically relevant AI: Right AI-automation tech right-purposed for right outcomes, with right processes, by right people.  

Why THESE services?

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

 Top Emerging AI Trends we cover (Future-ready AI):

  • Next AI: Green/ Super-AI, federated-edge AI, AIoT, AcquiIP
  • Composite, confidential, formative, neurosymbolic AI

How to AI: EXAMPLES

Who we are

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

We are proud practitioners of AI & automation, each of us with 25+ years of hands-on experience. Having been part of 1000's of client projects on AI-automation-SM, it's time we share our learnings & IP's.

PRACTITIONERS

Why are AI-IA practices different from IT services?

Currently, there are no uniform process frameworks, architecture & best practice guidance on AI

AI-automation-AIoT assets, solutions and services are quite different from typical IT infra and apps services, in many ways. Traditional frameworks like ITIL, ISO 20000, COBIT etc. don't address many of the specific strategic, design, operational issues in AI-IA, such as:

  • Unique AI Strategy & Business Cases: Speed vs. cost of services- peer-benchmarked
  • Unique AI FinOps: Cannot drag & drop conventional service costing models, SLAs, pricing
  • Change, configuration, ops, support management processes for AI & automation are drastically different on data, components, SLM, performance, from typical IT services

AI-automation practice white-spaces

Why AI & automation assets & services require different process management frameworks?

Traditional frameworks like ITIL & ISO 20000 don't address many issues in AI-automation management:

  • Strategy, technology & provider selection 
  • Relevant skills, resources, experience, performance, KPI
  • Tectonic shift in culture- what computers did 70 years ago. 


The internal challenges within the AI & automation solutions tech-stacks

 The change, configuration, release management processes for AI-automation are different from typical IT service assets:

  • Major changes in training & testing data
  • Workflow changes
  • Changes in hyper-parameters & algo's

AISWITCH: Translating jargon to job-done

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

  • Patented best practice frameworks for AI-automation
  • Templates for setting up and running AI-automation CoE's 
  • Evaluation, negotiations with tech vendors & service providers

AI-Automation-AIoT Tech Research: CTO, CIO, IT SP's

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

  • Quarterly updates: Technology, algo's, competitive analysis
  • Latest AI technology and algorithms application analysis
  • Best practice guidance for AI-automation strategy offices

Client stories from service providers

AI-Automation-AIoT-AIOps Practice: End-User CoE, CXO's

Client stories from service providers

  • AI-automation-AIoT platforms/ solutions, services, people & process capabilities set-up, 
  • Market positioning, branding, 
  • Rewarding innovations

About Us

Research Advisors, Reviewers, Contributors

Acknowledgement


  • First and foremost, sincerest thanks to end-user and SP client leaders and AI/digital/ emerging tech consulting practitioners, and our ex-Gartner fellow research leaders, for peer-reviewing AISWITCH research notes and also acting as the crucial bouncing boards. For 25+ years, within Gartner, and then at other companies, they have been stalwarts in the areas of AI-automation, DevOps & agile, Asset Management practices & tools, ITSM and ITSCore- Gartner's proprietary maturity assessment toolkit. 
  • We are also pulling in young researchers interested in and well aware of AI, especially from hands-on coding and applications standpoints, to code for the patents and to write foundational blogs on the most relevant AI tech, applications and governance. Students & freshers in 15-25 age-group from prestigious programs of the best academic institutions (e.g. XLRI, IITs, IIMs) must be encouraged in AI practice research.


We the senior practitioners must become better listeners and solicit futuristic ideas on AI. We must practice what we preach- design thinking, lateral thinking, viewpoint engineering, scenario planning and speculative design, by actively soliciting participation from young minds. 

Ian Head, Chief Research Advisor

https://www.linkedin.com/in/ian-head-245168/

Prof. Paul Morrissey, Chief AI Advisor

https://www.linkedin.com/in/prof-paul-morrissey-69856/?originalSubdomain=uk

Dr. Tapati Bandopadhyay, Chair & CEO

 https://www.linkedin.com/in/tapatibandopadhyay/ 


Email: bandopadhyay@aiswitch.org 

Sriram Krishnan, Chief Revenue Officer

https://www.linkedin.com/in/krishsriram/

Ashwin Gaidhani, Senior Advisory Leader

 https://www.linkedin.com/in/ashwin-gaidhani/ 

Email us: ras@aiswitch.org (RAS- Research & Advisory Services)

 admin@aiswitch.org (Operations & interactions)

Ashit Padhi, Director of the Board- Consulting

 https://www.linkedin.com/in/ashit-padhi-7b4a202/ 

AISWITCH: Why, What, How-to, For Whom

    Copyright © 2021 AISWITCH - All Rights Reserved.  


    Email us: 

    ras@aiswitch.org (Research & Advisory Services), admin@aiswitch.org (Operations)

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    • 5 DATASTORY TECHNIQUES?
    • TOP 5 DATA STORY TOOLS?
    • 3-MINUTE DATA STORIES?
    • WHAT'S YOUR AI STORY?
    • WHY BUILD 3-MNT AI STORY?
    • HOW TO BUILD 3-MNT STORY
    • POWER OF 3: DECLUTTER AI?
    • ALL RESEARCH BLOGS
    • AI PRACTICE- END USER
    • AI PRACTICE- TSP
    • FAQ- AISWITCH USAGE
    • WHO WE ARE