Artificial Intelligence as a Managed Service | Opportunity for GSIs

AIaaMS | Artificial Intelligence as a Managed Service | Opportunity for GSIs

Artificial Intelligence : It’s “Now But How” and Not “Sometime Somehow”

AI has caught fancy of people like nothing else in perhaps the whole of human memory. It is part of almost every discussion everywhere. Be it WEF / Davos or every Corporate Board rooms or most living rooms in our homes or inside the classrooms of any school. And fairly so. We seldom see a technology so profound offering such promises that could impact every human in so many ways. Mostly positive.

While consumer-side adoption of AI has fueled the desire for its implementation in governments and enterprises, real mojo in the equation is coming of age of the underlying ecosystems. People are happy with the creative outcomes (essays, texts, images, videos what have you) via GenAI applications, an enterprise (Government or Corporate) still need a lot more than these apps to be really able to monetise the value of AI.

Adopting AI is rather complex and demanding for any enterprise. Their lack of budget, skills, resources and limited knowledge makes it difficult for them to actually make AI a ground reality. For many, if not most, it can remain just a fancy mission statement on their corporate strategy slides rather than a tool that adds value to their employees and customers.

The complexity here is akin to healthcare environment where most of medicines, know how and infrastructure might be openly available but for us to get a proper treatment for an ailment, we need qualified doctors and established hospitals we can trust, who can bring all these medicines, knowledge and equipment’s together to actually treat us properly.

Enterprises need to tackle a lot of complexities in building blocks across AI Software, AI Developer Tools and AI Infrastructure layers. In cloud terms these are classic SaaS, PaaS and IaaS layers with their full might of inherent complexity topped up with specialised AI tools like Data / Models, Classifier, Services, Domain Specific Learning Models, Training and so on. In itself, setting an AI system up is hugely overwhelming, for even a highly sophisticated technology provider. Setting up a yet to be trained AI system can be so arduous task that it can easily throw an organisation off track from their core business.

This problem presents an incredible services opportunity for the Global System Integrators who have been on the vanguard of solving technological and process complexities for their customers across the globe for over than three decades now. Top 15 GSIs employ over 2.5 Million people spread across the globe so their skills at scale, domain expertise, technical compliance and geographic reach places them perfectly at the cusp of this market opportunity where they can add an unprecedented value for their customers.

Following the healthcare service delivery example, GSIs could offer Artificial Intelligence as a Managed Services (AIaaMS) where customers get a pre-built AI system that is pre-trained  on the generic industry / vertical use cases ready to be fine tuned with customer's specific data / processes / practices, in an aaS Model. This will bring significant economies of scale to shorten the value realisation runway for the customers and maximise returns from their AI investments.

As Global System Integrators (GSIs) today offer many of these solutions and services as part of their AI or Vertical offerings any which way, all they need to do is package these in domain aligned AIaaMS catalogue, thereby freeing up customers to focus on their core business and GSIs abstracting all platform design, build and run complexities for customers. A Win Win.

Moreover One AI Fits All approach will not suffice for most customers and like their hundreds of use case specific business applications, they will need use case specific AI systems to augment or replace their current applications. This will add another layer of complexity. With the ecosystem relationships that GSIs thrive on, they can help build an ecosystem of multiple AI systems integrating to deliver one large Intelligent Platform for all customer needs.

Another aspect of getting a truly productive AI system is Domain Specific Model Training on data specific to enterprise in question while addressing necessary data privacy needs. This is where GSIs skills at scale can come handy to assist customers in data annotation, training the models on customer data and other services. This will further accelerate value realisation for customers.

So, essentially delivering a Private AI system that make Best of Breed AI components easily consumable where customer pay as they use for the outcomes they attain, AIaaMS can be a critical enabler.

AI or Not to AI, that’s not a question anymore.