AI Practice Research Advisory

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

The Sunk Cost of Wrong AI Strategy

What are the risks that can make your Enterprise AI Strategy go wrong?

Top 5 AI Strategy Risk Factors:

AI strategic goals are not aligned to business and organizational strategies
AI strategic outcomes are not clearly defined
AI technology glidepaths and potential technology/ TSP/ vendor lock-ins are not factored in hence AI strategy is not agile enough to sync with speed of tech progress
AI strategy communications frameworks are not clear, hence the required culture shift for adoption@scale are not happening/ at risk
AI strategy is not backed up/ synced up with AI workforce planning hence execution is at risk

What are the top 5 dependency factors for AI strategy to be successful?

Culture fit: It's nothing to do with technology. The mindset to change needs to be prepped up and cultivated first. The demand needs to emerge from within. Experimentation and gamification with AI need to be rewarded as the desired behaviour. Top leadership must recognize these innovative trends across the strata of the workforce, and must be seen actively encouraging people at all levels doing AI right.
Top leadership dedication: AI IS A CEO/ CXO AGENDA. There's no escaping it, no matter which business you're in. All the successful peers are actively pursuing unique AI strategies to win. Top leadership awareness and commitment to AI practice maturity, is a must.
AI practice maturity of technology and service provider ecosystems: There are strong dependencies between your AI practice maturity and that of your service providers/ partners/ tech vendors. Pracrtice maturity doesn't come just by having access or ability to pay for AI technology stacks. Practice means how good you are in deploying the AI technology stacks that you've invested in, to achieve your strategic targets. That is where your providers' maturity will make or break your AI journey.
AI leverage and practice maturity of your business suppliers: AI maturity of your suppliers and distribution channel partners and logistics service providers can greatly affect your own supply chains and distribution efficacy.
AI budget vs RoI visibility: This is a critical internal dependency given that AI is expensive both to build and to run and augment. The continuous RoI and real cash flow impact in dollar value, be it on profitability to productivity, topline to bottom-line indicators, need to be made visible at all times, to the CFO and Board of the organization. Shelf life of relevant AI is short for its expenses in an enterprise. Therefore successful AI strategies have a critical dependency on a 'Continuous Business Case and RoI" approach.

Top 3 CSFs - How do you know your AI strategy is working?

Top 3 Critical Success Factors when you know your organizational AI strategy and investments are working as you expected and committed:

Top leadership has clear visibility of strategic outcomes of major AI projects
Culture of the organization becomes AI-first ie more than 80% users switch to AI-Powered workflow options instead of sticking to old inefficient n ineffective ways of manual workflows
No vendor lock in: Your AI strategy is flexible and agile enough to quickly change and adopt, to stay relevant and competitive, to take advantage of new algorithms and new techstacks.

These CSFs are achieved when the AISWITCH AI Practice Maturity Model is successfully put in place, and the organization's AI Practice Maturity is above level 3 at least.

That's Why: 10K+ AI Practice Leaders view this guidance

VISIBILITY: 10K+ research views

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. In partnership with global research & advisory firms like ISG, F&S, Third Eye, AISWITCH helps build AI & data practice bridges between end-user leaders and their TSP partners: e.g.

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.

Really, how good is your AI?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

7 example service providers have been assessed in terms of their AISWITCH AI practice maturity, with a focus on GenAI- hype vs. value. Base: Primary data- examples, secondary research

Are you able to DISRUPT AI or DISRUPT WITH AI?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

Ask yourself as an Enterprise AI practice leader- be in tech or end-user organizations. What are you disrupting? If the answer is just incremental me-too rat race with linear innovations, then there's NO AI there- as Turing explained...

How are you playing the Platforms game?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

How are you playing the Platforms game?

If you are still working on or are providing services for the red ocean steps, it's a long way ahead. But the blue ocean is truly limitless...

The AI Tech inflection point

Ways to Monetize & Fund your AI

How are you playing the Platforms game?

Here's a detailed AI Tech Prediction Curve on what to expect in the near horizon 2025 to 2028.

Ways to Monetize & Fund your AI

Getting the fund allocated for AI is a tough task for CAIOs/ CIOs/ CDOs. Creating an AI Innovation/ Opportunity fund, internal to the enterprise, can be a game-changer.

Are you an AI-first CEO/ CXO?

Ways to Monetize & Fund your AI

If not, the future looks more grey than green. Why must AI be a CEO/ CXO agenda? Because it is THAT important for any company's basic competitive survival today.

'I think, therefore I am': AI

Why does AI fail?

AISWITCH- Dark Data to Light

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:

73 million jobs are to be automated by 2030 (McKinsey)
AI to create 500K jobs by 2020, 2 million by 2025 (Gartner)
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- Dark Data to Light

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

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

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

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

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

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

What we delivered: AISWITCH at work

GTM Templatization for one of World's Largest Cloud SPs

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

For new cloud solutions and services, developed their strategic GTM on AI, data and cloud governance for their large and exemplary client enterprises, and market storytelling practices using the AISWITCH framework

6 months AI practice advisory engagement - to create the AI storyboarding practice and initial GTM collaterals

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Enterprise Cloud Strategy (Roadmap, Target outcomes and Balanced Scorecards- financial/ Customer/ Internal/ Knowledge outcomes,
Strategic Risk assessment & mitigation process, cloud cost and financial management process),
Workforce (training and upskilling requirements, CoE org structure and RACI, roles and JDs), Information (Data) strategy- PII, risk management, cost of data infrastructure),
Technology (Roadmap, upgrade cycles, risk, cost- finops), Culture (organizational change,
Communication-CUDA system, team metrics, gamification),
Human augmentation metrics (operational, risk, business parameters)

1 year research, advisory and consulting engagement on AI practice assessment, competitive benchmarking, AI strategy formulation and process set-up, best practices and usecase discovery, usecase priority matrix

Research Partner of Global Firm & ITSPs on Data-AI-Cloud services

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Information/ Data management and Technology management processes

Leading all key AI-cloud technology platforms quadrant research projects for a leading global research firm
Analyzing cloud and AI practice maturity of the platform ecosystem partners- large ITSPs
Innovation roadmap evaluations of cloud and AI service providers in the US region
Technology (Roadmap, upgrade cycles, risk, cost- finops), Culture (organizational change), Communication-CUDA systems, team metrics, gamification)- related AI adoption advisory for all major ITSP clients, as a Research Partner of the firm
Providing advisory and guidance on defining, benchmarking, assessing and running AI-Human augmentation metrics (operational, risk, cost vs. business value parameters for ITSP clients and internal functions)

~5 years- Continuous research, advisory and consulting engagements on cloud and AI practice assessment, competitive benchmarking, technology and usecase evaluations, talent quality benchmarking, strength of strategy & storyboards assessments, research IP's and collaterals development for ITSPs

Setting up AI Information/ Data management and Technology management processes

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up AI Information/ Data management and Technology management processes

AI Information (Data) management processes (DataOps, ModelOps, data relevance and staleness mgt, new algorithms and retraining cycles management, additive vs incremental training cycles, DLCM, DRM- data risk mgt- security/ privacy/ data governance regulations by regions)
AI Technology management - Chip2Experience fullstack tech management processes- lifecycle and utility management from hardware to appstacks to services to experience layers, infra risk/ regulations management, AIFinOps- cost management using Cloud Providers FinOps tools platforms)

Performed detailed multi-year assessments and maturity benchmarking of AI technology and information (Data) management practices in 7 large Telco's of 7 countries, as part of a corporate network

4 years periodic assessments, benchmarking - internal peer-based and best practices/ innovations of competition from different geo's, discovery of strategic disruptive AI opportunities in Telco in specific markets and regions

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Enterprise AI Strategy and Governance minimal process framework for AI services clients: Establishing AI governance process templates to be used as a prioritized set of best practices, by Clients
- AI strategy & governance management processes (financial risk assessment, strategic outcomes management, business risks mitigation),
- AI Workforce management process (CoE development- different structures set-up- centralized vs federated/ distributed, Training@scale, adoption, change management, skilling, partner management),

Performed complete assessment and benchmarking with industry competitors, and then set-up the global AI Strategy Management Process, defined the AI Strategy along with the AI Leaders at US and UK, in the Strategy Formulation Process: For a top global CPG company- 1 year engagement

Setting up & running AI-Data-Cloud Success storyboarding templates for SP/ SI partners

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Developing Customer success storyboards using AISWITCH- GTM of AI services: Using the AISWITCH 6 dimensional Framework to articulate and present customer storyboards on exemplary customers from different sectors including BFSI, consumer services, new-age digital companies like Swiggy.

6 months AI strategy - business case development and storyboarding practices using the AISWITCH TM framework

Setting up AI Culture & Human Augmentation Metrics: Processes, assessments, benchmarks

AI culture management (Communication- establishing CUDA framework on AI GRC, shared risks- responsibilities-accountability and metrics, collaboration and team building- hybrid teams of tech+ business functions, pi-shaped people profiles)
AI for Human Augmentation (Outcomes Metrics- Human productivity impact, better GRC metrics, improved Green metrics of techstacks)

Performed the adoption management and culture and metrics definition processes starting with assessments, peer benchmarking and best practices discovery, within multiple entities in the Telco network for a regional telecom giant

3 years advisory engagement periodically, to drive change management- processes and people practices, metrics and RoI- process guidance

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 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.

AI PRACTICE RESEARCH: AI-Cloud-Platforms Expert Partner- ISG, F&S, AWS

AI PRACTICE RESEARCH: AI-Cloud-Platforms Expert Partner- ISG, F&S, AWS

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

Why are AI-IA practices different from IT services?

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

The Sunk Cost of Wrong AI Strategy

What are the risks that can make your Enterprise AI Strategy go wrong?

What are the top 5 dependency factors for AI strategy to be successful?

Top 3 CSFs - How do you know your AI strategy is working?

That's Why: 10K+ AI Practice Leaders view this guidance

VISIBILITY: 10K+ research views

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

Really, how good is your AI?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

Are you able to DISRUPT AI or DISRUPT WITH AI?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

How are you playing the Platforms game?

GenAISWITCH Scores: GenAI Practice Maturity Radar for 7 ITSPs

How are you playing the Platforms game?

The AI Tech inflection point

Ways to Monetize & Fund your AI

How are you playing the Platforms game?

Ways to Monetize & Fund your AI

Ways to Monetize & Fund your AI

Ways to Monetize & Fund your AI

Are you an AI-first CEO/ CXO?

Ways to Monetize & Fund your AI

Ways to Monetize & Fund your AI

'I think, therefore I am': AI

Why does AI fail?

AISWITCH- Dark Data to Light

AISWITCH- Dark Data to Light

AISWITCH- Dark Data to Light

AISWITCH- Dark Data to Light

AISWITCH- Dark Data to Light

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

Who we are

Practical guidance on AI-automation implementation

Practical guidance on AI-automation implementation

AI-automation practice white-spaces

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

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

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

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

Client stories from service providers

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

Client stories from service providers

What we delivered: AISWITCH at work

GTM Templatization for one of World's Largest Cloud SPs

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Research Partner of Global Firm & ITSPs on Data-AI-Cloud services

Setting up AI Strategy Development Process Templates for a world's largest CPG/ FMCG

Setting up AI Information/ Data management and Technology management processes

Setting up AI Information/ Data management and Technology management processes

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up AI Information/ Data management and Technology management processes

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up & running AI-Data-Cloud Success storyboarding templates for SP/ SI partners

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up standardized AI Strategy & Governance Processes, maturity assessment & industry benchmark

Setting up AI Culture & Human Augmentation Metrics: Processes, assessments, benchmarks

Setting up AI Culture & Human Augmentation Metrics: Processes, assessments, benchmarks

Setting up AI Culture & Human Augmentation Metrics: Processes, assessments, benchmarks

About Us