Online Degree in Blockchain
Blockchain Council
February 11, 2019

Global Tech Council
Global Tech Council
January 01, 2019

Certified Artificial Intelligence Expert

Udemy
Udemy
January 01, 2019

Certified Autonomous Driving Professional

Certified Post Merger Integration Specialist
IM&AA
May 01, 2018

A comprehensive body of knowledge on M&A Integration

Blockchain Council
Blockchain Council
May 01, 2018

Certified Cryptocurrency Expert

Institute for Mergers, Acquisitions and Alliances (IMAA)
Institute for Mergers, Acquisitions and Alliances (IMAA)
May 01, 2018

International M&A Expert

CryptoCurrency Certification Consortium (C4)
CryptoCurrency Certification Consortium (C4)
April 01, 2018

Certified Bitcoin Professional
Issuing authorityCryptoCurrency Certification Consortium

Blockchain Council
Blockchain Council
April 01, 2018

Certified Blockchain Expert

IIB Council
IIB Council
April 01, 2018

Certified Blockchain Professional

M&A Leadership Council
M&A Leadership Council
January 01, 2018

Certified M&A Specialist

ISACA
ISACA
February 01, 2009

Certified in the Governance of Enterprise IT (CGEIT)

EC-Council
EC-Council
January 01, 2002

Certified Chief Information Security Officer

International Due Diligence Association
International Due Diligence Association
January 01, 2002

Certified Due Diligence Professional

InterimExecs
InterimExecs
January 02, 2001

Certified Interim Executive

Turnaround Management Society
Turnaround Management Society
January 02, 2001

Certified International Turnaround Manager (Level C)

Institute of Management Consultants USA
Institute of Management Consultants USA
January 05, 2000

Certified Management Consultant

Alliance of M&A Advisors
Alliance of M&A Advisors
January 05, 2000

Chartered Mergers and Acquisitions Professional

Alliance of M&A Advisors
Alliance of M&A Advisors
January 04, 2000

Certified Mergers and Acquisitions Advisor

Project Management Institute
Project Management Institute
January 02, 1998

Project Management Professional

Fellow
Aspen Institute
June 11, 2020

Metaverse Fashion Council
Fashion Coin
May 05, 2022

Forbes Technology Council
Forbes
November 22, 2019

EC-Council C|CISO Board
EC Council
November 15, 2009

Decentralized Platforms: Existential For Web3 In Enterprises
Import from medium.com
May 04, 2022

Decentralized platforms, the new paradigm essential to operationalize Web3Continue reading on DataDrivenInvestor »

Web 3.0: The Go-to-Market Inversion
LinkedIn
April 13, 2022

The hype around Web 3.0 is astounding nowadays and most of us agree that neither definitions nor standards are clear yet. However, a lot of its critics come from the linear era where they built products, used sales teams to sell them, and centralized revenue and profits. It has been harder for many folks attuned to the linear thought process to understand the exponential technologies, decentralization, or network effects on steroids such as Web 3.0. I have tried to outline the counterintuitive aspects of Web 3.0 which cause resistance within the old economy mind.

The Metaverse: Hype vs Reality
Import from medium.com
January 15, 2022

IntroductionContinue reading on DataDrivenInvestor »

The Metaverse: The 8 Key Technology Drivers
Import from medium.com
January 03, 2022

The key technologies driving the MetaverseContinue reading on DataDrivenInvestor »

M&A Due Diligence: Spotting the Dark Cloud
Import from medium.com
December 22, 2021

The risks and opportunities with cloud computing during M&AContinue reading on DataDrivenInvestor »

M&A Deal Leakage
Import from medium.com
December 22, 2021

IntroductionContinue reading on Mergers, Acquisitions and Divestitures »

Legal AI: An Automated Versus Autonomous Future
Forbes
July 27, 2021

Corporate legal departments have historically been resistant to automation and technology adoption, but the effects of the pandemic forced many to shift gears and pursue, or at least actively consider, more automation for legal activities. Artificial intelligence (AI) has been the cornerstone of this strategy, and mapping key investments to business outcomes remains a challenge.

Spotting the 5 Common Crypto Price Manipulation Patterns
Import from medium.com
July 26, 2021

Understand cryptocurrency market manipulation techniquesContinue reading on DataDrivenInvestor »

Decoding the Uniswap Controversy
LinkedIn
July 26, 2021

The decentralized exchange, Uniswap shocked the crypto community last week when it unilaterally announced the delisting of certain tokens from trading. This is against the ethos of blockchain and cryptocurrencies i.e., centralized power and concentration of influence. A prominent DeFi player doing this activated thousands of people protesting on social media and upheaval in Telegram groups.

DeFi Protocols: Designing for Value
Import from medium.com
July 22, 2021

How to accrue value to protocolsContinue reading on DataDrivenInvestor »

Common Crypto Manipulation Techniques
LinkedIn
July 21, 2021

Market manipulation has existed for as long as tradable assets have existed and cryptocurrencies are no exceptions to it. The cryptocurrency space is also immature with nascent regulations making it vulnerable to market manipulations not easily possible with mature markets. In this article, I will dive into some of the common market manipulation techniques, identify patterns around it and equip people to spot abusive behavior.

Spotting the 5 Common Crypto Price Manipulation Patterns
LinkedIn
July 21, 2021

Market manipulation has existed for as long as tradable assets have existed and cryptocurrencies are no exceptions to it. The cryptocurrency space is also immature with nascent regulations making it vulnerable to market manipulations not easily possible with mature markets. In this article, I will dive into some of the common market manipulation techniques, identify patterns around it and equip people to spot abusive behavior.

Stablecoin Quality Analysis
Import from medium.com
July 10, 2021

The stability of stablecoinsContinue reading on DataDrivenInvestor »

Stablecoin Quality Analysis
LinkedIn
July 05, 2021

Old economy minds consistently toot the volatility of cryptocurrencies making it the biggest point of criticism. Stablecoins challenge that argument by providing consistency in value, they are “collateralized” i.e., the total value of stablecoins is backed by assets held in reserve. More often they are pegged to the value of fiat currencies like USD, Euro, Yen, etc., but they can also be pegged to values of other commodity assets like oil, gold, etc.

The Shitcoin Phenomenon: The New Bane of Crypto
Import from medium.com
June 29, 2021

Anatomy of shitcoins, the good, the bad and the ugly.Continue reading on DataDrivenInvestor »

Oracle Crypto Assets: A Quick Primer
Import from medium.com
June 28, 2021

Understand Oracles, the unique cryptocurrency class.Continue reading on DataDrivenInvestor »

The Shitcoin Phenomenon: The New Bane of Crypto
LinkedIn
June 26, 2021

Welcome to the era of “Shitcoins,” where new investors who missed out on getting rich with Bitcoin are being taken for rides by online jokesters pushing coins with ultra-creative names and no clear value proposition. The FOMO (Fear of Missing Out) psychology is exploited to the hilt.

Oracle Crypto Assets: A Quick Primer
LinkedIn
June 25, 2021

As the DeFi movement accelerates, decentralized applications and smart contracts require a lot of real-world information which they cannot access independently given restrictions imposed by Blockchains. Specifically, on DeFi, derivatives, insurance, and trading all require external inputs to function in an accessible format, the accuracy and relevance determine the value of a smart contract. Any errors will make the smart contract lose value and if the data trail is not auditable, sources not transparent or not reversible, the immutability of the blockchain further exacerbates the problem.

How Crypto Whales Move Markets
LinkedIn
June 22, 2021

Investing in cryptocurrencies is a relatively new trend, it requires looking at these assets through multiple lenses. We must analyze technical chart indicators like support levels, resistance, bull flags, Bollinger bands, and RSI, etc. When everyone, including seasoned institutional investors, uses the same indicators and tools to take profits ahead of time, leaving average retail investors high and dry. While investing in an array of tools and an arsenal of sharp minds are things beyond an average retail investor, there are small things one can do like going beyond basic technical analysis, understanding crypto fundamentals deeper, analyze the coordinated media FUD quickly for its content, timing, and intent, etc.

Bitcoin Bull Markets, 5 Key Metrics
LinkedIn
June 20, 2021

There has been a lot of news on Bitcoin lately with a ton of panic due to media FUD and bull’s euphoria. The market capitulation of May 19th dumped a lot of coins, they do get time to get picked up, and eventually, we will be fine in a few weeks as accumulations complete. The stock-to-flow model still shows a fair price of $57,000 for a bitcoin and this has not gone wrong even if they're delayed catchup, the catch-up always completes. But emotions apart, let us take a dispassionate view based on fact, data, and metrics.

10 Insights from Cryptocurrency 2.0
LinkedIn
June 15, 2021

Crypto is not for the faint-hearted. I will not go into all the popular stuff you are reading and observing e.g., this is institutional investor play, the cycle is different, regulators are getting more comfortable, etc. Instead, let me provide observations from my own vantage point and insights gained from the network.

Tokenomics: Measuring Quality of Crypto Assets
LinkedIn
June 13, 2021

The coming of age for the entire crypto market has occurred in this cycle with the asset class attaining its age of adolescence. This is the only value-creating asset class outside the traditional, inefficient, and old financial system. Crypto assets have unparalleled user privacy, decentralization, no intermediaries, and they cannot be censored or shut down.

Demystifying Cryptocurrencies: Exploring the 5 Distinct Asset Classes
LinkedIn
June 06, 2021

Cryptocurrencies are a true product of the digital age, they are not managed or governed by central authorities like banks, governments, or middlemen and can operate efficiently without them. This asset class has evolved so rapidly that it has created confusion amongst many others. The very use of the term “altcoin” has outlived its use as crypto assets have evolved into roles where they are not alternatives to Bitcoin, nor will they ever be.

A Perspective on Complexity Reduction
LinkedIn
June 04, 2021

Almost every executive today, be it a CEO of a global multinational firm, a CEO of a startup, or a business leader speaks about the complex environment they operate in today making their jobs more stressful than 10 years ago. This so-called complexity is only going on rising with globalization, multiple regulations, disruptive business models, new competitors, changing customer preferences, and a plethora of technologies, etc.

4 Pillars of Modern M&A Integration
LinkedIn
May 31, 2021

Over the last few years, the rules of business have changed a lot. Technological shifts have been exponential spawning out new business models, older incumbents have been left behind or are trying to acquire themselves into the modern era.

Prototype vs. MVP: Myths and Realities
LinkedIn
April 23, 2024

Lately, I have had many founders come and pitch for funding or seek advice on how to raise capital. Many seemed unclear on MVP vs. Prototypes and have been confusingly using them. A lot of them did not understand that it is an uphill battle trying to raise money on a prototype and more so in today's economic climate.

Board Member
Thinkers 360
October 20, 2020

Executive Advisor
Casper Labs
October 08, 2020

Operating Partner
Diode Capital
October 01, 2020

Appnomic
Appnomic
October 01, 2019

CEO and Board of Director of Appnomic, an AI based self-healing enterprise company

SmartBeings Inc
SmartBeings Inc
July 01, 2018

SmartBeings is a silicon valley based startup & creator of WooHoo , an award-winning Voice AI Assistant for Enterprises. WooHoo brings the convenience of voice AI technologies to enterprises through its Voice-as-a-Service ( VaaS), Facial Recognition & a Cloud-based AI Platform. WooHoo is the worlds first integrated AI Assistant that combines the power of Voice AI Technologies with IOT, converting voice into actions and delivering the personalized and intuitive user experience.

SmartBeings Inc designs AI-driven IoT products and platforms to solve real-world problems utilizing AI, deep learning, voice-based technologies (incl. NLP & acoustics), facial recognition, security & data encryption, and cloud connectivity.

Crosby
Crosby
May 01, 2018

Ec Council IoT Board
EC-Council
January 18, 2017

M&A Due Diligence & Integration: A collection of unique topics and lessons from the trenches
Independently published
March 30, 2021

The business has changed a lot over the last decade, but M&A has largely remained the same without adapting much, there are many new areas, new approaches, and these new scenarios but have no formal literature around them. This book sheds light on some of the new and the different strategic and tactical aspects of M&A.

Getting to the Partner Level: A practical guide for Management Consultants
Independently published
March 30, 2021

Getting to the Partner Level is a practical guide for Management Consultants who are interested in learning how to make it to the Partner level and being successful at that level. This book includes insights into what makes a good consultant, how you can be more effective at work, and tips on how to navigate your career. You will also learn about the different types of Partners out there and how they operate. This book includes a lot of helpful information that will help you along your journey as a consultant from foundations to being successful at the highest levels in the profession.

CEO3.io - Driving Exponential Change: Sell before you have a product, execute agile pivots when required and scale up exponentially
‎ Independently published
March 24, 2021

Too many legacy companies are being disrupted, many iconic brands from the last century have faded into oblivion and many went bankrupt.These failures are mainly attributed to their inability to understand the transformative nature of digital businesses, exponential technologies, understand disruption and pivot at the right time. Both of us have experienced the speed of disruption; from vantage point of working in legacy companies and leading and operating disruptive companies. Nitin also spent time in Management Consulting working with both, the disruptors and the disrupted. Maarten witnessed disruption while at Nokia and recently held an innovation leadership position in a large European insurer. Unless more companies go digital, many industries will be disrupted and will affect many families. We hope to share a few of our experiences, observations an expertise to help executives make the transition.

Audiobook: Wargaming for M&A Integration Leaders
Dealsroom
January 03, 2019

Develop foresight, startegize and execute under uncertainity, prepare the integartion teams for disruption and course correction

American Business Award for the Book "Getting to the Partner Level"
American Business Awards
March 04, 2017

The Art of M&A
McGraw Hill
November 12, 2019

Subject Matter Expert on AI Based Valuations

Modern Approach to M&A Integration
M&A Science
October 24, 2020

Wargaming for M&A Integration Leaders
FTI Consulting
December 19, 2017

Getting to the Partner Level: A Practical Guide for Management Consultants
IMC
August 06, 2015

Institute of Mergers and Acquisitions
IMAA
March 04, 2019

Co-Founder
Mergeflo
May 09, 2022

MergeFlo, M&A integration software in PLG Motion

Co-Founder
zbyte
May 07, 2022

zbyte is creating a new category in the blockchain ecosystem: the decentralized platform (dPlat). dPlat allows dApp developers to build on existing protocols via a low code/no code platform. It enables Web 3.0 ecosystems by removing the complexity for developers and enterprises to build dApps. The zbyte dApp store creates a thriving ecosystem of developers and users by allowing them to upload dPlat enabled dApps that leverage public blockchain.
zbyte Pro has created modules on dPlat to allow Fortune 5000 companies to integrate existing enterprise Web 2.0 ecosystems into Web 3.0. zbyte pro enables enterprises to easily build dApps with the security, immutability, transparency, and privacy offered by blockchain with predictable transaction costs and no cryptocurrency on their balance sheet. zbyte's customizable hybrid blockchain infrastructure leverages all the benefits of a permissionless blockchain while providing privacy and price predictability of a permissioned one to enterprises at a fraction of the cost.

Innovator of the Year
International Business Award
August 11, 2018

M&A Consultant of the Year
Finance Monthly
August 01, 2018

honor description Received for pioneering new approaches of Platform and Blockchain M&A

Consulting Executive of the Year
CeoWorld
June 02, 2018

Top Consultants of 2018
CEO Today Magazine
May 01, 2018

ICMCI representative to the UN
ICMCI
February 21, 2017

40 under 40
The M&A Advisor
May 25, 2012

Certified M&A Specialist
M&A Council
January 03, 2019

CEO Worldwide
CEO Worldwide
April 01, 2010

Certified Interim CEO (iCEO)

IMCB International Management Consultants Certification Board
IMCB ™ International Management Consultants Certification Board
April 01, 2010

Master Management Consultant

Certified M&A Advisor
Alliance of M&A Advisors
January 05, 2010

(ISC)²
(ISC)²
February 01, 2002

Certified Information Systems Security Professional

150+ Top Global Cloud Thought Leaders and Next Generation Leaders of 2021
Whizlabs
April 19, 2021

It is loud and clear that Cloud Computing is fundamental to the new wave of digital transformation. In the year of 2020, with everyone working from home, better cloud storage and computing strategies have helped many organizations to grow higher while some were struggling to adapt to the changes. This is where the Cloud Thought Leaders and Next Generation Leaders stepped in. With immense presence in social media and public forums, many of the leaders have shared their views, the struggles they have faced and the ways they have overcome professionally as well as personally.

Top 50 Influencers: Cryptocurrency
Thinkers 360
April 01, 2021

Top 50 Influencers: Business Strategy
Thinkers 360
December 31, 2020

CX Influencer
Thinkers 360
December 12, 2020

RPA Influencer
Thinkers 360
November 03, 2020

Top 50 Influencers: RPA (Oct 2020)
Thinkers 360
October 20, 2020

Top 50 Influencers: Blockchain
Thinkers 360
October 08, 2020

Top 50 Influencers: HR
Thinkers 360
October 02, 2020

Top 20 Influencers: Change Management
Thinkers 360
September 21, 2020

Top 50 Influencers: HR
Thinkers 360
September 11, 2020

Top 50 Influencers: RPA
Thinkers 360
September 09, 2020

Top 10 Influential CEOs
Beyond Exlamation
September 02, 2020

Top 50 Influencers: RPA
Thinkers 360
September 02, 2020

Top Thought Leader on M&A
Thinkers 360
August 23, 2020

Top 50 Influencers: Cloud (Aug 2020)
Thinkers 360
August 21, 2020

Top 50 Influencers: 5G
Thinkers 360
August 18, 2020

Top 50 Influencers: Customer Loyalty
Thinkers 360
August 12, 2020

Top 5 Influencers: Autonomous Drivig
Thinkers 360
August 08, 2020

Top 10 Influencers: Digital Disruption
Thinkers 360
July 14, 2020

Top 50 Influencers: Cloud
Thinkers 360
July 02, 2020

Top 50 Influencers: Change Management
Thinkers 360
June 30, 2020

Top 5 Influencers: Strategy
Thinkers 360
June 29, 2020

Top 10 Influencers: Autonomous Driving
Thinkers 360
June 22, 2020

Top 50 Influencers: VR
Thinkers 360
June 18, 2020

Top 50 Influencers: AI
Thinkers 360
June 16, 2020

Value of Data in Autonomous Driving: A Fireside Chat with Nitin Kumar, CEO
Women in Big Data
October 21, 2020

The 6th Annual Internet of Things Global Summit
Forum Europe
October 04, 2018

Thank you to the 200+ participants and speakers who have joined us over the two days of The 6th Annual Internet of Things Global Summit.



The Summit returned to Washington D.C on 4 - 5 October. This series of discussions, idea sharing, and networking was an opportunity to join the debate from the inside. For the first year, the event was free to attend to interested parties from the IoT community.

Digital Transformation: Insight Based Selling
ABB
January 23, 2018

Hostile Takeovers: The Dark Side of M&A
The Growth Academy, Munich
January 25, 2011

A perspective on hostile takeovers. The presentation covers definitions, attack, defense, techniques and best practices. A subject that does not have much literature available in the public domain and a subject rarely talked about.

US district judge strikes down Trump’s new H-1B visa rules
Hindu Business Line
December 03, 2020

AI trend and predictons
Thinkers 360
October 03, 2020

Self Healing Pioneers
Enterprise World Magazine
September 05, 2020

Appnomic eyes Investment
Business Line
August 12, 2020

Hotels to cut Outsourcing
The Economic Times
August 04, 2020

Rethinking Smart Manufacturing
Teletech
July 30, 2020

Linkedin Etiquette
Darpan Magazine
July 28, 2020

Cisco Racism Case
Economic Times
July 28, 2020

Heal Thyself: Self Healing Enterprise
Business India
July 27, 2020

Donald Trump Exec Order on H1B
Business Line
June 24, 2020

Marketing Change: COVID 19
Forbes
June 10, 2020

Rethinking Smart Manufacturing for the New Normal
IoT World
May 26, 2020

Forbes Interview: Software Graveyards
Forbes
May 23, 2020

Appnomic: A Pioneer In Creating Self-Healing Software For IT Operations
Enterprise World
May 19, 2020

Digital Transformation needs Business Models
Forbes
May 17, 2020

Point of View on Self-Healing Entreprise
UpTech
May 14, 2020

Technology Innovation
UpTech
May 14, 2020

Digital Literacy Training Can Align Emerging Technologies
IoT World
May 01, 2020

Self Healing Entreprise
Forbes
April 29, 2020

Why Industrial Automation Security Should Be a Renewed Focus
IoT World
April 27, 2020

As industrial organizations grapple with COVID-19 fallout, automation has become an even hotter topic. Experts fear, however, that the acceleration of automation could drive unforeseen consequences for organizations that don’t focus on security...

Don’t Forget Security-by-Design Principles in Times of Trouble
IoT World
April 23, 2020

US Revisits Immigration Guidelines: COVID-19
The Business Standard
April 21, 2020

The Indian IT services industry is awaiting details of US President Donald Trump’s impending move to suspend immigration, in light of the pandemic.
Though details of the executive order are awaited, the IT industry is not likely to be affected much in the near term, given that mobility is already restricted. However, any sweeping change in regulations could affect moving human resources from India to the US over the medium term, according to industry sources...

Post Covid-19, IT-BPO players see new business opportunities
Business Line
April 15, 2020

Covid-19: IT companies brace for disruption of service delivery model
Business Line
April 07, 2020

Appnomic: A unique product, from insight to foresight
Silicon Review
April 01, 2020

Separation Management Office
M&A Science
October 01, 2002

Silicon Valley's Magnificent Four
Master Communicator
November 06, 2020

Divestitures: A Strategic Perspective
M&A Science
June 10, 2020

Hiring M&A talent for the new era
M&A Science
April 22, 2020

Corporate M&A Summit
C-Parity
October 13, 2016

Leading with Impact
Master Communicator Podcast
May 12, 2020

Grow it Forward: The Business Pivot
Advantage Talent
May 12, 2020

M&A Science:Modern Day Integration
M&A Science
January 03, 2019

Divestitures: Transition Services Agreements
M&A Science
October 08, 2020

IoT Venture Investing and Global Trends
IoT World
June 29, 2020

What Does it Mean to Go Digital?
Forbes
May 11, 2020

M&A Risk
Forrester
May 05, 2009

A Framework to evaluate Cyber Risk in M&A transactions and minimize integration risks

Disruptive Change
Georgetown University
August 21, 2020

Faculty: IMAA
Institute of Mergers, Acquisitions and Alliances
April 03, 2019

Webinar Modern Day M&A Integration Adapting to the new world order in an era of disruptive change
MergerWare
January 06, 2019

The business world has changed over the last decade, M&A integration has not kept up. A perspective on how to adapt to the new world order

Platform M&A: The Integration Frontier
MergerWare
January 03, 2019

Divestitures:Value Capture Through IT Disentanglement
CEO Worldwide
December 12, 2010

https://www.ceo-worldwide.com/whitepaper/wp000011-EN.pdf

Product Value Leakage: The Services Mindset
Thinkers 360
October 19, 2020

Anatomy of Go-to-Market Motions
Linkedin
October 08, 2020

Product Management: Art and Science of Hiring
Linkedin
August 07, 2020

Turnaround of Failed M&A Integration Efforts
Linkedin
August 01, 2020

Autonomous Driving: Mobility Data Challenges
Linkedin
July 04, 2020

Hostile Takeovers: The Anatomy
Linkedin
July 02, 2020

Understand Client Personalities
Linkedin
June 26, 2020

Autonomous Driving: The Big Data Value Myth
Thinkers 360
June 25, 2020

Hurting the Network- Part 3
Linkedin
June 20, 2020

Autonomous Driving: Technology Stack Implications
Thinkers 360
June 15, 2020

The Stack Attack
Linkedin
June 14, 2020

Value Based Selling
Linkedin
June 10, 2020

Hurting the Network- Part 2
Linkedin
June 08, 2020

Hurting the Network- Part1
Linkedin
June 06, 2020

Edge Computing: Drivers and Trends
Linkedin
June 02, 2020

Anatomy of Software Graveyards
IMC USA
May 06, 2020

Every product has a finite life, some live longer than others. This article provides insights into the anatomy of the software graveyard journey.

Effective Selling: Understand Customer Personalities
Slideshare
February 15, 2020

Hostile Takeovers: The Dark Side of M&A
Slideshare
January 27, 2020

Modern Day Sales for Management Consultants
SlideShare
January 22, 2020

M&A Strategy and Integration
FTI Consulting
January 03, 2019

Wargaming for Chief Information Security Officers
EC-Council
January 01, 2019

Wargaming for CIOs
EC-Council
January 01, 2019

IoT Driven M&A
FTI Consulting
December 06, 2018

India’s Offshore Industry: A Disruptor getting Disrupted
FTI Consulting
November 14, 2018

A Perspective on the Internet of Things
FTI Consulting
October 08, 2018

Metaverse: The Legal Tech Impact
Thinkers360
January 25, 2022

Introduction

Ever since Facebook announced its rebranding as Meta and the pivot into being a Metaverse company, it has created a lot of buzz and hype. The announcement also woke up several Metaverse initiatives, projects, and companies off the radar. The Metaverse is considered an amalgamation of digital realms where people can interact, socialize, communicate, collaborate, and even conduct commerce. This concept itself is not new and prior Metaverse incarnations like Second Life have been around for a decade or more.

Given VR (Virtual Reality) has proved multiple standalone experiences that gathered momentum over the past few years, these experiences would now be woven together to produce a more coherent Metaverse, where digital and physical objects and beings will interact seamlessly.

The Metaverse is gearing up to become the fourth-generation compute platform i.e., the first generation of applications ran on the PC, second generation on the world wide web, and the third generation on mobile phones. Spatial computing, as it is called, is growing in its promise and it is a matter of time until it will deliver value at scale for the practice of law.

Range of Use Cases

The three-pronged adoption curve with quick-hit use cases driven by consumers, corporates, and other organizations creates opportunities for law firms and legal service providers. Now, the low-hanging use cases for everyone is considered marketing, however, a lot more opportunities are on the anvil. Let us examine some specific legal use cases, nuances, and barriers to adoption in this article.

Borderless Legal

Many high-profile, international cases could hold public trials in the Metaverse and even in the jurisdiction of where the crime occurred. Jurors and witnesses with VR headsets could be participating in the trials, and meetings with clients could be more engaging and immersive. Courts could be replaced with digital spaces eliminating the constraints of physical space, processing multiple cases in parallel with people’s ability to go in and out of spaces at will.

Crime Scene Recreation

VR enabled Metaverse imparts the immersive ability for legal professionals to move past whiteboards and sticky notes, and experience direct immersion into an accident, crime scene, or recreated scenarios that mirror real life. During deposition, legal professionals, experts, witnesses, jurors, etc. could be in the same room as the testimony wearing VR headsets.

Professional Training

Metaverse training can enable witnesses, jurors, lawyers, and even judges to walk a crime scene to understand context, intricacies, possibilities, and train themselves quickly on complex cases. Through the utilization of a metaverse, a shared digital experience, individuals could ‘live’ the experiences discussed in a court proceeding instead of just hearing about them. This could lead to a potentially deeper understanding of a case and change how our legal system operates.

Legal Education

Through the use of a metaverse, the legal education system could open their classrooms up globally and students would not be restricted by geographic constraints. The curriculum could also be adapted to be highly immersive, with students experiencing cases unfold firsthand, rather than just reading about them in a textbook. Also, students could experience VR simulations of trials, court cases, and courtrooms, enabling them to gain valuable hands-on experience that may otherwise be difficult to obtain.

 

 

 

Litigation Management

Although critical rules and laws regarding evidence need to evolve so modern technologies can be accommodated, the possibilities are real. Judges and juries can go through details of the evidence directly experienced during a crime scene, creating better empathy and fairness in the system. Depositions can become more effective where scheduling, location, and time zones become a critical path. Metaverse-enabled ecosystems will reduce costs related to space, interviews, depositions, discovery, etc. making the economics easier for clients and attorneys.

Sentences and Punishments

The Metaverse can also produce unpleasant environments instead of soothing experiences. Many of these environments can be designed for sentences or punishments as an outcome of the trial. These virtual environments can provide milder sentences or corrective measures for juvenile delinquents or others.

Immersive Collaboration – Metaverse

A metaverse can be effectively leveraged without being in one location, as it is not subject to geographic constraints. This use case is suitable for global or multi-location teams on time-sensitive matters, cases requiring detailing, standardized procedures e.g., M&A, contract negotiations, etc. Clients can also be dispersed globally and effectively collaborate with law professionals via an immersive experience.

Marketing

The legal services economy i.e., law firms and service providers can use VR for marketing via promotions and advertising. There are a few different avenues for this ranging from affiliate advertising, VR client experience, case simulations, thought leadership, etc. Over the next 12-18 months, it is probable that everyone with a website on the internet will scramble for a Metaverse presence, as the rush has commenced with daily news articles around large enterprises establishing their footprint.

Barriers to Adoption

Although many of these use cases appear cool, the big barriers will need to be addressed legally, commercially, and operationally to remove barriers of adoption. There are limited to no VR workspaces dedicated to running legal operations in corporations or law firms we know. The legal industry is traditional and where change is voraciously resisted and justified in the name of legal risk itself, it has historically been challenging to introduce radical shifts into the legal industry. There are multiple barriers to adoption which will need to be addressed. Let us examine prominent issues below:

Technology Asymmetry

Leveraging VR technology is not easily accessible financially or operationally for everyone. If one plaintiff or defendant cannot financially afford this technology, then one party could be a victim of technical asymmetry putting them at a disadvantage.

Forensic Maturity

VR forensics is new, emerging, and fast-paced, and when scaled to multiple and interwoven experiences such as the Metaverse, it becomes extraordinarily complex. The maturity of this domain is nascent and lacks enough domain specialists, making widespread adoption harder.

Change Management

The time, effort, and resources deployed to make the Metaverse acceptable in the courtroom can be non-trivial. VR is a radical departure from traditional e-discovery and procedures will need to be amended to allow the use of rendered evidence. Many legal professionals will be averse to embarking on this arduous task.

Cost of Infrastructure

The cost of deploying metaverse infrastructure is high and requires considerable investment. The infrastructure includes servers, 360-degree cameras, hardware, software, trained personnel, etc., and many public courts and law practices are unlikely to see viable returns or advantages from these investments. Technology in VR is fast-maturing and will see short upgrade cycles adding to these costs in the near term. It will take time to provide the required computing power at the edge (not the cloud).

 

 

Medical Limitations

The Metaverse generates highly immersive technologies which can pressure the physical attributes and conditions of people. People have felt motion sickness, disorientation, and risk artificial sensory overload. People with mental ailments like anxiety and autism also could be challenged with the technology and due considerations must be accounted for before assuming the use of Metaverse becomes universal.

Privacy Concerns

Accessing VR via mobiles or headsets can compromise privacy ranging from location to retinal access. The ambiguity around privacy laws in the Metaverse will hinder adoption. Bodysuits provide opportunities to create more data about the user e.g., body language, emotions, health, behavior, reactions, etc. There could also be surveillance bots deployed to identify individuals via faces, fingerprints, retina, gestures, walk, or even their Metaverse footprints.

The Dark Side of The Metaverse

As promising as a shared virtual reality may sound and as real as the barriers are, one needs to remember there will also be a need for laws pertaining to Metaverse crimes which must be established. Although still in its preliminary stages, the Metaverse is already a fertile ground for a range of crimes from extortion, money laundering, terrorism, prostitution, stalking, child abuse, identity theft, etc. Traditional law is yet to come to terms with all this even if the harm and implications caused by virtual worlds are understood to a fair degree. Lawyers, psychologists, etc. are looking intricately at the boundaries between actual crime and virtual crime depending on the damage caused. Many questions are yet to be answered e.g., a sexual assault on another person in a virtual world may cause mental trauma rather than it being a physical violation, and hence how should it be treated?

The rules of conduct also get reconfigured in metaverse environments by attaining superpowers e.g., flying, invisibility, shapeshifting, etc., and could add new dimensions to the set of crimes possible in the realms of physical reality. Even if the risk of being murdered, raped, or being physically assaulted in the Metaverse is low, the lack of actual consequences could encourage people to engage in such acts causing psychological trauma to the victims.

What can be done today?

Given the immaturity of the Metaverse, any legislative attempt to regulate it will be error-prone and may also cripple the innovative evolution of technology. Metaverse companies should self-regulate themselves, the environments, and the interaction models by adhering to ethical and legal principles to the extent possible. Governments and legislative bodies can proactively extend local privacy laws to contain the information collected in various Metaverses. Liability definitions must be clarified, and early blueprints of Metaverse laws must be developed quickly. In this decade, disruptive technologies will scale rapidly and exponentially, hence we may not have several years to address the risks and harness the opportunities.

Concluding Thoughts

The Metaverse is here is to stay, scale and grow. Industries like Media, Healthcare, Military, etc. have all embraced VR to enhance their customer insights and experiences from planning surgeries, training, mission simulations or helping first responders with risk reduction. The use cases outlined above so promise that it is a matter of time before barriers are removed driving endless possibilities through the adoption of Metaverse in the Legal industry. As the modern technologies power the new future filled with metaverses, artificial intelligence, autonomous operations, etc., the traditional legal industry must establish laws governing these new virtual worlds which intersect with the existing physical world.

About the Author

Nitin Kumar is a two-decade veteran in the Hi-Tech industry. His career has spanned many intrapreneurial and entrepreneurial roles in executive positions across Software, Services, and Management Consulting. His passion is propelling organizations to greater levels of success through strong relationships and differentiated products. He is considered a business builder, thought leader, and pioneer of many innovative approaches. During his operating and consulting roles, he has grown, transformed, and pivoted many software businesses and scaled businesses successfully. Nitin is the CEO of Ligl, a pioneer in digital discovery orchestration and is an author of many articles, and is often seen speaking at conferences on AI, IoT, SaaS, and Blockchain. He is a veteran CEO and has added value to 1,000 plus M&A transactions in his career.

 

Sources:

The Metaverse and its impact on the legal industry (thegreatblawg.co.uk)

The Metaverse: Hype vs Reality. Introduction | by Nitin Kumar | Jan 2022 | DataDrivenInvestor

https://abovethelaw.com/2021/12/is-this-the-first-law-firm-in-the-metaverse/

The Metaverse: The 8 Key Technology Drivers | by Nitin Kumar | Jan 2022 | DataDrivenInvestor

AI Enabled e-discovery: Expectations vs Reality
Thinkers360
August 04, 2021

As we rewrite the rules of business in this decade, artificial intelligence (AI) assumes the limelight. Legal professionals believe that a lot of promise offered by AI in law is unproven with several use cases unable to deliver. However, one area easier to embrace, adapt, and prove is digital discovery (erstwhile called e-discovery). It involves AI, other analytics, automation of workflows to handle new sources of data, expanding volumes, and additional capacity for legal professionals.

AI-Enabled e-discovery

Given the volumes of data, both structured and unstructured that lawyers must otherwise manually analyze, AI can have a drastic impact on the actions, outcomes, costs, and efficiency of each case. According to American Bar Association, 62% of lawyers already use some variant of traditional e-discovery solution and this level of adoption is easier to AI-enable and automate unlike other legal use cases of AI.

AI Use Cases in e-discovery

AI can reduce the burden on legal professionals by identifying patterns, relevant phrases, sentences prone to omission when traditional methods. There are many low hanging opportunities with AI and e-discovery, let us discuss a few below:

Case Research

AI helps sift through high volumes of data to identify key documents and associated information adding speed and efficiency to legal teams. It can also benchmark whether a claim is legit, strong, or worthy. If terabytes of data can be analyzed to chart the strength of the case to focus on what matters, it is worth its weight in gold.

Structuring Data

Managing an e-discovery case is complex, there are numerous documents and facts with a lot of details e.g., contract scope, date of the breach, ramifications of violation, etc. Using clustering techniques, AI can group patterns of terms that appear together while creating multiple angles on each case issue. Unstructured data being clustered into logical packages for analysis simplifies the data and imparts speed that humans cannot achieve.

Technology-Assisted Review (TAR)

The most cumbersome and expensive part of e-discovery is the review stage. AI can expedite classification, tagging, relevance, etc. AI also learns from human actions for additional keywords or facts of interest and this additional data can train review models for higher ranges of accuracy which limits the time humans have to spend on these mundane tasks.

Digital Discovery Analytics

The discovery process is intense and deep, people can lose sight of their depth of analysis and go past the point of diminishing returns. These efforts add costs are rarely quantified, compared, or improved. KPIs correlation activities, costs, and financials are seldom analyzed for productivity, efficiency, or returns. AI can compile this information in real-time and roll it up into a visual layer eliminating recurring problems and enhance the cost efficiency of the entire function.

Data Redaction

Data redaction is one of the key concerns e.g., PII, consent, etc. Withholding data and privileged, anonymous, redacted, etc. is time-consuming and AI alleviates this issue. Shielding data from disclosure with high accuracy and greater levels of compliance is another important use case for AI in digital discovery.

Risks and Opportunities

There are several risks and opportunities with using AI in digital discovery, we can however categorize them into two broad themes with opacity being a perceived risk and cost being the opportunity.

Cost Reduction

AI enables substantial savings on the e-discovery spend by cutting human effort, avoiding rework, reducing errors, and imparting speed. Smaller and less complex cases can be optimized by automating research, reviews, redaction, etc. AI can also bring forth effort and spend patterns through real-time analytics enabling focus and operational decisions.

Explainability Risks

When data is limited, expensive to collect, or in unknown formats, it becomes prohibitive, and hence, traditional rule-based, automation workflows could prove better than AI. On top of this, cost, access, and limitations of data can affect accuracy. It takes massive amounts of data to train AI models. These constraints push legal departments back to legacy methods.

Finally, the opacity within algorithms creates a lack of explainability. Clarity by explainability is one of the most important factors in decision-making and a major area of discomfort for lawyers.

Future of AI-Enabled e-discovery

AI use cases are rapidly evolving and changing the way the e-discovery process is designed, operationalized, and delivered. The future brings multiple shifts to this space.

Native AI

Today, AI is layered on top of existing discovery processes i.e., it is not native to it. The integrations into ESI (Electronically Stored Systems) must be deeper. The extraction of information, categorization of data, clustering, and contextualization by case will be seamless in the future. Deep learning algorithms will simulate human thinking and the e-discovery software (not the AI module) will learn to learn driving exponential value.

Upstream Adoption

AI must be leveraged more upstream in the EDRM process, deeper integrations will enhance visibility into data sources before collection. In the future, AI will deploy sophisticated data mining algorithms to widen scope outside of ESI and correlate them with context, custodians, and anomalies. These algorithms will inform AI-based recommendation engines to identify additional custodians to be involved or placed on legal hold without compromising defensibility. Pushing AI more upstream will create significant downstream efficiencies by reducing data volumes sent out for review. Integrating AI upstream will also allow legal teams to set case strategies and tactics as legal teams transition from insight to foresight.

AI-Enabled Orchestration

AI will evolve from its tactical roles today i.e., collector, curator, advisor, etc. to an orchestrator. AI will strengthen its role as an advisor through recommendation engines proposing additional documents, custodians, etc. In the future, AI will be an orchestrator learning from past actions, correlating actions and decisions across multiple channels. For example, if the relevance rate of document review was X% then AI will help fine-tune the collection parameters, this learning can be leveraged to target the collection and map them to the right reviewers. AI, as an orchestrator will also help automate tasks, predict case, and sentence outcomes based on its own learning.

Concluding Thoughts

AI creates a range of opportunities for legal professionals to drive value in digital discovery. E-discovery is more suitable with acceptance higher than other areas of Legal Tech for using AI as it eliminates mundane human tasks like targeted collection, early data assessment, relevance, issue categorization, and quality control while preserving human bandwidth in areas of higher value.

About the Author

Nitin Kumar is a two-decade veteran in the Hi-Tech industry. His career has spanned many intrapreneurial and entrepreneurial roles in executive positions across Software, Services, and Management Consulting. His passion is propelling organizations to greater levels of success through strong relationships and differentiated products. He is considered a business builder, thought leader, and pioneer of many innovative approaches. During his operating and consulting roles, he has grown, transformed, and pivoted many software businesses and scaled businesses successfully. Nitin is currently the CEO of Ligl, a pioneer in digital discovery orchestration and is an author of many articles, and is often seen speaking at conferences on AI, IoT, SaaS, and Blockchain. He is a veteran CEO and has added value to 1,000 plus M&A transactions in his career.

 

Voice Tech: Ways to Play
Thinkers360
October 11, 2020

[Image by Gerd Altmann from Pixabay] Voice technology has come a long way in the last five years. Organizations and consumers have adopted voice technologies like text-to-speech, automatic speech recognition, natural language understanding, natural language generation etc. for mundane tasks through complex automation. In this article, I try to bring forth some insights around Voice Tech and possible business models.

Introduction With any new technology, adoption and usage make the journey from emerging to being mainstream and voice is clearly crossing that chasm. Apple, Google, Baidu have reported hundreds of millions of devices using voice, and Amazon has 200 million users. Adoption is typically uneven, but the penetration levels of smartphones accelerate that journey when it comes to Voice Tech. Given voice is not used in the same way by everyone, it creates opportunities to spread across context and experience continuums to find a sweet spot for deeper adoption. Use cases, context and method of access matter and playing a big role- voice adoption also differs by how people access it. While voice assistants are the media favorites, smart phones, in car assistants etc. are also very prevalent and scaling.

Altering Business Paradigms Voice is literally changing how business works and customers think about products. Especially given we are in the middle of a global pandemic, the contact-less use cases have suddenly scaled by replacing touch intensive graphical user interfaces or buttons. With platform players like Siri, Alexa, Cortana, and Bixby creating broader use cases, the enterprise players like Nuance, Houndify etc. create niche opportunities with white labelled solutions. The crowding of this market creates risk of rapid commoditization, but value is always created by context, user relationships and customer experiences which build the importance of skills like VUX (Voice User Experience) and VUI (Voice User Interface) specialists. Poor experiences can jeopardize use relationships, contaminate the brand, and impede adoption. Misunderstanding voice-based requests (poor ASR or NLU) can pollute the context itself e.g., answering an out of context question due to misinterpretation. Let us examine a few such improvements, these will enable various business models in the voice arena.

Boost Customer Interactions One of the goals of voice technologies is to develop deeper personal relationships with the users and customers. The level of personalization possible with voice is much higher than the graphical user interface or the chatbot era. The sheer variety of systems, context and behaviors are the biggest challenge to automation or unified customer experience, voice can play a huge role in integration the technology ecosystem of hardware, software, and service together.

AI Enabled Automation The convergence of Voice Tech and Artificial Intelligence create a myriad of opportunities as Voice Tech benefits from machine learning. AI is going to be embedded deep into the context enabling voice interfaces to easily leverage the scale. For examples, voice assistants can teach themselves how to solve problems better and quicker with your customers.

Sonic Marketing Voice Tech is well on its path to be front and center of search engine optimization. It has started to migrate organizational thinking from text-based to voice-based SEO. As voice-based searches continue to increase, sonic marketing strategies must weave themselves around voice. Sonic marketing is more than search, it also spans voice content e.g., podcasts and sonic branding i.e., using audio to reinforce brand recognition. Voice-enabled ads provide advertisers with real-time measurement capabilities, enhancing the appeal of sonic marketing. Lack of in-house skills and knowledge make it a bit hard for early adoption of voice-based marketing strategies, but there is wide acknowledgement of the large opportunity it presents.

Voice Enabled Products Voice has morphed from being a small feature on a smartphone to being able to control large ecosystem of products and services. They can eliminate the issue of multiple apps on multiple devices and siloed operation of ecosystems. Customers expect products to have native integration with their platforms of choice. All new generation products will have to be voice enabled for them to stay relevant and competitive.

The COVID-19 Catalyst Coronavirus has provided an ideal catalyst to voice adoption. Given concerns on the spread, everyone from retail stores, to banks and hotels etc. have either created or planning contactless products, services etc. Voice technologies provide the perfect alternative to touching buttons or screens to interact and transact.

Business Models Voice Tech is the unifying glue between a single ecosystem or multiple ecosystems enabling efficient distribution and monetization. Voice is also a way to quickly weave service economics around hardware or software. Voice can create voice enabled hardware infrastructure to drive larger adoption, create software modules to help developer communities to voice-enable applications or enhance existing services to provide better integration with products in the ecosystem.

Platform Based Platform plays have been around for a while, it is about creating of a seamless interaction on a two-side marketplace and monetize transactions. Ability to gain critical mass on each side of the platform and engineer interoperability, interconnections through meaningful curation is the key. The hardware market is very disparate e.g., bulbs, plugs, home appliances etc. Voice assistants can make the integration seamless; the business model eliminates the need of many separate mobile applications into one voice interface. The key is to get as many hardware vendors to adopt the platform while driving adoption by the users leveraging platform business model. Monetization can be attained through the hardware vendor or the user, for now most cases are the former paying for services while user paying for voice enabled hardware like Alexa or Google Assistant.

Voice First Business Models As voice adoption scales with voice only applications or voice enabled hardware, platforms will amplify reach, monetization, and scale by enabling third party solutions like marketing, analytics, security, automation etc. Almost all the Big-Tech players have embarked on creating such ecosystems to scale. KPIs to measure these ecosystems have been around # of skills e.g., Alexa, usage of skills, transactions enabled by ecosystems, # of ecosystems enabled e.g., smart home, smart car etc.

Transaction Based Business Model The transaction-based business models have been popular for a while, we can see voice-based transactions scaling across value chains such as payments, advertising, marketing, food delivery etc. The basic economic value underpinning the business model is a piece of the transaction fee, this can get to significant levels of scale as ecosystems grow their reach. The transaction-based business model can scale across hardware, software and services creating new experiences across complete value chains for companies and consumers alike.

Voice-Data Interchange Model The voice and data interchange are a great way to monetize Voice Tech. The difference between voice and data being most data generated by sensors today are monetized by sensor creator, but voice is monetized by parties other than the creators. In future, I see the advent of voice brokers aggregating queries from multiple sources and monetizing them as packaged intelligence. For examples, voice archives can become an archived investment to corelate with data patterns as augmented intelligence for better targeting etc. There is also a market for real time voice commentary, such as weather, disaster, traffic jam information etc. One of the emerging business models is micro- monetization of voice e.g., AaaS or “Answers as a Service”

Conclusion Voice is a fast-growing interface enabling better experiences through automation, integration and weaving service economics around hardware and software ecosystems. Voice Tech is at the crossroads between multiple context, intelligence and experience continuums and will continue to scale and evolve. There do exist a few barriers and challenges to overcome such as voice privacy when it is aggregated by cloud players, lack of fully baked data sets in the right volumes to train models in the enterprise, voice security still being immature and limited open source communities etc.

Autonomous Driving: The Big Data Value Myth
Thinkers360
June 25, 2020

A lot has been said about data being the new oil and gold etc. Data value cannot be generalized, its intrinsic and monetizable value varies. In this article, we explore the value of data and what makes it valuable, through the autonomous driving lens.

Autonomous Driving Technology Stack: Configurations, Implications & Insights
Thinkers360
June 16, 2020

Implications of choices made by autonomous vehicle providers

Migrating from Traditional Monitoring and APM to Self-Healing: A case for EBITDA improvement
Thinkers360
May 07, 2020

By Nitin Kumar & Cuneyt Buyukbezci, Appnomic According to Gartner, legacy monitoring tools still have approx. 30% of market share, this is a lot of investment for reactive measures, lack of full visibility with no preventive and remedial measures. Migration from APM and traditional monitoring tools to self-healing creates EBITDA improvement by rationalizing tools and headcount, automating operational processes, and reducing hardware costs. In addition, self-healing ensures business continuity (outage elimination) through early warning preventive healing. Migration to self-healing also improves productivity by cutting down false positive alerts, and resource time invested in troubleshooting. Such dramatic impact is due to value shift in five operational levers. Migrate from MTTR to MTTP/MTTI Business risk, operational cost and productivity impact of repairing problems is always higher than preventing them. Preventive self-healing leverages artificial intelligence to shift metrics from MTTR (Mean Time to Repair) to MTTP (Mean Time to Prevent) and MTTI (Mean Time to Identify) eliminating cost and risk attributed to system failures. Eliminate alerts Alert storms make it hard to identify the key insights towards IT operational stability, the issue is more profound if quality and completeness of data is lacking. Too many legacy tools, in too many different parts of the enterprise are detrimental to analyzing root cause, create operational inefficiency and higher downstream costs. Preventing issues before they happen will generate less noise and more efficiency. Understand visibility gaps and address them An average of eight to ten tool are deployed to monitor parts of the IT stack and yet a holistic picture is elusive. Visibility gaps cause undetected issues making it difficult to triage the problems and eliminating root causes. Self-healing observes the behavior of the users and the entire technology landscape (applications to infrastructure) creating a full picture. Autonomous Prevention and Optimization IT has been equipped with automation tools to configure systems and shift workloads. However, decisions and triggers still rely on human judgement and intervention. Self-healing can autonomously detect issues before they happen, decide the right triggers and actions leading to autonomous elimination of problems. Right size capacity Due to lack of visibility into workloads and correlation to system behavior, companies overprovision hardware to accommodate the largest incoming workload. Self-Healing provides Complete visibility and correlation between applications, systems and workloads creating an opportunity to write size hardware and thereby reduce spend. For many enterprises that are stuck with the legacy monitoring and APM tools self-healing offers EBITDA improvement opportunity by changing paradigm in operations by improving service levels while eliminating cost and complexity.

Self Healing Enterprise
Thinkers360
January 05, 2020

A self-healing system is an always-on operation running 24/7. Self-healing systems can prevent software problems by addressing causes before they turn into problems which impact service. A self-healing enterprise should have predictability to detect signals for potential issues, isolate those issues with precision, determine root causes and resolve them automatically before they lead to service disruption or degradation. All of this is enabled and enhanced by AI-driven autonomous IT operations software. Self-healing systems have foresight allowing them to predict where issues might arise in the future, saving IT teams both time and expensive resources. Self-healing enterprises can capture value from three drivers by elevating user experience, optimizing resources and ensuring business continuity. A self-healing enterprise can record material improvements in its customer experience compared to its peers. Self-healing systems can reduce unplanned outages leading to improvement of brand perception and protection. They can also eliminate performance issues from the online user journey. Finally, high transaction businesses such as e-commerce, banking, telecommunications and pay per use services can increase their customer acquisition by reducing user abandonment. A self-healing organization can be created in three steps. First, once implemented, AI can learn the ins and outs of capacity models and then maintain them. It can determine underutilized or overutilized software components and adjust to the environment and its context. AI can simulate expected workload changes based on growth projections. This first stage is commonly referred to as projected healing with use of AI-assisted prevention. Second, AI predicts issues by proactively analyzing software modules to look for early warning signals. This analysis highlights the most important performance metrics and includes forensics data helping triage the cause of early warning signals. These analyses inform proactive healing actions e.g., adjusting system configurations or writing additional scripts to automatically heal the issues. This second stage is commonly referred to as proactive self-healing. Third, autonomous self-healing augments all the capabilities from the first two levels, adds independent action. At this stage, an enterprise can execute the entire healing cycle automatically by detecting warning signals, predicting problems and rectifying the issues which caused the warning signals in the fi

Strategy, M&A, Biz Dev, Board Member | CEO, Autonomous IT Operations

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CEO, former Management Consulting Partner, Board Member with expertise in Strategy, Business Models, Disruptive Tech and M&A veteran