Generative AI for Enterprises – Don’t Hype, Adopt Simply
There will be very few who will disagree that Artificial Intelligence (AI) is the biggest disruption after Cloud in the world of IT and business models at large globally.
AI has been evolving over many years now with an ever-increasing set of terminologies:
a. Monikers like Intelligent AI, GenAI, Agentic AI, etc.
b. Model Types like Machine Learning, Supervised Learning, Unsupervised Learning, Deep Learning
c. Branches like Computer Vision, Fuzzy Logic, Expert Systems, Robotics, Machine Learning, Neural Networks/Deep Learning, Natural Language Processing
d. Models & Assistants (Chat BOTs) like ChatGPT, Gemini, Deep Seek, Claude, Manus, etc.
To add to these AI-related vocabulary, there are also 7 commonly agreed Types of Artificial Intelligence (Source Credit: Sunny Betz)
1. Narrow AI: AI designed to complete very specific actions; unable to independently learn.
2. Artificial General Intelligence: AI designed to learn, think and perform at similar levels to humans.
3. Artificial Superintelligence: AI able to surpass the knowledge and capabilities of humans.
4. Reactive Machine AI: AI capable of responding to external stimuli in real time; unable to build memory or store information for future.
5. Limited Memory AI: AI that can store knowledge and use it to learn and train for future tasks.
6. Theory of Mind AI: AI that can sense and respond to human emotions, plus perform the tasks of limited memory machines.
7. Self-Aware AI: AI that can recognize others’ emotions, plus has sense of self and human-level intelligence; the final stage of AI.
While AI has been evolving rapidly with huge progress wrt technology and theory, the practical aspects of AI (How to Use AI) however has mostly not landed firmly on the ground yet. If one asks a CXO or a CIO about AI, almost all will enthusiastically say “YES, we are Using AI”, but when probed further most will get into generalizations without getting into the specifics of What, Why, How, etc.
It’s like a “déjà vu” moment with what happened with “Digital Transformation” – everybody started talking about it, but there was no common articulation or set process of “How to Do Digital Transformation”.
The fact remains that no matter how disruptive or revolutionary a new technology may be, until and unless it adds demonstrable, repeatable and significant value to businesses (through business cases, ROI, etc.) wrt Business Growth/Transformation/Modernization, it will just end up being another hype or jargon.
In this article, I (while upfront declaring that I am no expert on AI) will attempt to filter out all the hype, hoopla and noise about AI/Gen AI – while laying out my viewpoint about a simple, common-sensical and business-contextual “2-Steps” way of adopting this useful technology evolution by enterprises, irrespective of their size, geography spread and industry vertical. I will also elaborate on a potential low-hanging fruit which can be the first use case for Gen AI adoption.
STEP 1: PROOF OF THE PUDDING (The Appetizer)
Identifying the first use case (aka low hanging fruit) for GenAI adoption while ticking off the following considerations:
✭ It will address a business problem which is visible and organisation-wide
✭ It will deliver significant business benefits
✭ It will entail least/a low risk of regular business disruption
✭ It will ideally be in the control/domain of IT department
✭ It will not require existing technology/platforms/tools to be replaced or disturbed
✭ It will align with the existing & future overall technology direction, architecture, landscape and Cybersecurity posture
✭ It will have the attention of the Top Leadership/Management
Once a use case is identified applying the aforesaid criteria, a thorough Business Case needs to be documented and approved through the organization’s approval/stage gate processes. The business case needs to cover the following:
a. Business problem to be solved
b. Quantification of the business problem
c. Cost of adoption/implementation
d. Quantification of business benefits & also Qualitative benefits expected post adoption
e. ROI expected
STEP 2: ROLLOUT ROADMAP & EXECUTION (The Main Course with Dessert)
With the first proof point successfully delivered (after business case re-validation, post the implementation), next logical step would be to:
1. Identify the next set/list of use cases and create a rollout roadmap based on priority/business case/stage gate approvals
2. IT Team can work with other business functions in the organization like Finance, Procurement, Supply Chain, Manufacturing, Sales & Marketing, Distribution, HR & Administration, etc. for identifying and detailing these use cases
3. Create Business Cases for each Use Case listed
4. Set up a “AI Centre of Excellence” (CoE) to rollout these GenAI use cases across the organization
5. IT Team can also take external help from consultants or tech service providers for this exercise, who can bring in expertise & partnership models like CoE Consulting & Staffing, IP Co-Creation, GTM for CoE as a Profit Centre, etc.
The goal and outcome would be to effectively enable the enterprise’s Business Transformation initiatives with Digital Transformation through new tech adoption
IDENTIFYING THE “LOW HANGING FRUIT” (First GenAI Use Case)
WHAT
✭ IT Support Tickets
WHY
✭ IT Support is a key function of IT as an enabler for business transformation
✭ It impacts both the revenue and cost sides of any enterprise irrespective of size, geography spread and industry vertical
✭ From an IT Service Delivery perspective covering Infra, Apps, Integration, etc. it impacts the daily work lives and productivity of internal stakeholders including end users across various business functions, IT support teams, outsourced vendor support teams) and also external stakeholders in cases where IT platform(s) access is given to customers and vendors
✭ IT Support, while “Keeping the Lights On”, also gets a significant allocation of the IT Budgets, ranging from 30%-40% in most manufacturing & distribution-oriented enterprises
✭ In most enterprises, COTS applications like ServiceNow, Fresh Service, Pager Duty, etc. and also homegrown legacy apps are used as tools for IT Support, with a combination of multiple tools being used is also common in enterprises
✭ IT Support Tickets are primarily of 2 types – Incidents and Enhancements, with Incidents comprising 60% – 80% of the total tickets raised
✭ In practical life, the quality of enhancements work unfortunately also leads to new Incident support tickets being added to the list
✭ Incident Support Tickets are commonly categorized wrt workflows/responsibilities like L1, L2, L3, L4 and also wrt complexity/severity like P1, P2, P3 etc.
✭ Metrics like Ticket Trends, MTTA, MTTR, SLA Violations, etc., are commonly used to govern the IT Support service delivery
✭ In most enterprises, an elaborate support team structure including internal and outsourced vendor support is in place
✭ In many cases, reinventing the wheel, i.e., solving “known incidents” are a major workload for these support teams, which ideally should be an end user self-service than a new ticket raised
HOW
✭ In the first phase of adoption (“BOT Agent with Human in Loop”), the BOT solution will enable/guide end user self-help for repeats of all “known” and “similar” support tickets.
✭ In the next phase of adoption (“BOT Agent Only/Agentic AI”), the BOT will execute “self-heal” or “auto-care” for repeats of all “known” and “similar” support tickets.
✭ Further, as & when “new/unknown” tickets are solved by the Support teams, the BOT will just need to get trained on these new incident resolutions
BENEFITS
✭ Lesser No. of Support Tickets being raised – enhanced end user satisfaction and productivity
✭ Lesser No. of Support Team (internal & outsourced vendor) required, with them being redeployed for enhancements or other productive IT tasks/projects – reduced IT support costs
✭ While IT Support platforms like ServiceNow, Fresh Service, Pager Duty, Azure DevOps, etc., evolve and may offer some Analytics & AI Automation wrt Self Service, that would be a hybrid approach and will entail significantintegration costs and additional licensing costs for giving access to all end users
✭ Sitting on top of these aforesaid multiple ticketing tools being used, the Gen AI solution will be like a single common abstraction layer – a single touchpoint for end users or support teams without the need to navigate across multiple tools
✭ This solution can also be tailored to align with the existing & future overall technology direction, architecture, landscape and Cyber Security posture
✭ It will entail least/a low risk of regular business disruption
✭ It will be in the control/domain of IT department
✭ It will not require existing technology/platforms/tools to be replaced or disturbed
✭ Unlike humans, the BOT can work 24x7x365 without fatigue and human errors
Disclaimer: The contents of this article are purely written in an individual capacity based on the personal opinions of the author. The author does not claim to be a SME on the topic covered in this article. Data sources and image credits have been duly cited, as and where applicable.
About the Author :
Mr. Subham Sarkar
Strategic Advisor,
Celebal Technologies
Agilitz Technologies
Netlabs Global IT Services
Jumpstart Ninja Technologies
Mr. Subham Sarkar is a business strategist, technology evangelist, thought leader and mentor.
Mr. Subham Sarkaris a senior leadership professional with around three decades of running career in the IT industry.
Mr. Subham Sarkar is on the Advisory Board of a few exciting early- and late-stage start ups.
Mr. Subham Sarkar With an MBA and Engineering education background, he had a passion for keeping himself abreast of the macro economics and dynamics of the global economy, how geo-politics and the ever evolving technology landscape are opening up newer possibilities and challenges for the present and the future.
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To help early- & late-stage IT start-ups scale their businesses globally and contribute to the IT Services eco-system of both consumers and providers
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Mr. Subham Sarkar ‘s earlier New & Emerging Technology Articles Published :
GenAI – A Case of Running with the Hare and Hunting with the Hounds ?
” Generative Adversarial Networks (GANs) – An AI & ML based Future ”
” Quantum Computing – This Hype is for Real! ”
“India – World’s Digital Economy Leader”
” How Artificial Intelligence is gaining greater levels of trust in elderly care ”
“All you need to know about Sentiment Analysis ”
“ Intelligent Automation in it’s Early Teens “
Mr. Subham Sarkar can be Contacted at :
Mobile : +91-81476 52280
Also read Mr. Subham Sarkar‘s earlier articles:
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