A growing trend I’ve observed is that many CXOs are coming up with strategies to leverage AI for accelerating in-shoring or in-sourcing. I believe that this trend will soon become a powerful force that will drive the IT industry’s transformation, if not outright disruption.
History of IT offshoring
Offshoring IT services has been an established practice for more than 50 years. However, approaches to offshoring have changed over time.
Until the 90’s, the offshoring approach was primarily driven by access to skilled resources rather than technology adoption. As a result, the focus was on how to manage large remote IT teams efficiently.
At the brink of the financial crisis around the year 2000, the cost of IT started becoming a vital discussion point for many publicly traded companies. This led them to outsource their IT function (primarily on the run side) to an offshore/low-cost location. This shift in approach needed a fundamental re-thinking of how IT services were delivered.
Service providers needed to drive high sales volume to increase revenue (if low-cost products were being offered, driving high sales volume was essential). IT services were expected to be available 24 x 7, year-round, and so IT team sizes grew. These factors led to a widely accepted belief that IT offshoring was most effective when large teams were deployed, and processes with a high degree of separation of duties were adopted.
Technology, the catalyst for change
In today’s landscape, technology, not processes, takes center stage. New, more efficient ways of working are making traditional models, such as large teams with different and separate responsibilities, obsolete. Technology is driving change, and processes are evolving to keep pace.
Consider some of the major technological innovations:
- SaaS and container-based applications
- AI for IT operations (AIOps) is also reducing the need for large support teams, while improving resolution times, increasing coverage, and overall customer experience
- Generative AI (Gen AI) in call centers is radically changing IT support experience
- Gen AI in coding is drastically reducing the need for large development teams
Today, team structures are guided by the now popular “two pizzas rule” (https://www.techtarget.com/whatis/definition/two-pizza-rule). This means that in a culture where teams are highly technical and focused, humans (not processes) play a crucial role in how IT is managed. Of course, 24×7 support is still a necessity more than ever, but this is where AI and Gen AI can make a real difference eliminating the need for large teams with varying skill sets operating round the clock. AIOps can eliminate the need for 24×7 teams and can predict issues before they happen, drastically improving IT services and improving business continuity.
We are in an era where close collaboration between AI and humans is driving continuous improvements in productivity. Throughout history, tools have increased productivity. Today, AI and Gen AI are the new tools of the millennium that will drive improvements in productivity exponentially, especially in running ITOps. SaaS, containers, AI, and Gen AI are fundamentally disrupting how ITOps is managed.
The bottom line is that we are living in an era where processes such ITIL are becoming obsolete due to their original design principles:
- Process-centric models are no longer valid. Today, technology is at its core.
- The need to manage “large” teams is no longer necessary since AI and Gen AI have increased human productivity, which in turn has reduced reliance on large teams.
- The Command-and-Control approach doesn’t hold true anymore. Human-machine interaction will increase productivity as well as innovation and value. The future is all about generating value, and not so much about controlling output.
The nature of the IT workforce is evolving. Qualified IT professionals do not aspire to do traditional IT operational support anymore, such as monitoring dashboards for long shifts. The present workforce does not want to operate in a command-and-control structure; they want to create value. This leads to creating an environment that adopts modern models like the SRE (Service Reliability Engineers) or the DevOps model.
Why is AI transformation not going faster in IT operations?
Right now, adoption is the major constraint. There isn’t a technology limitation; there is a ‘courage’ limitation. Many IT leaders are not willing to embark on the necessary changes to properly adopt these new technologies (AI and Gen AI). As explained in my previous blog Re-thinking IT Resourcing: Why AI Must Take Center Stage, many IT leaders are failing to adopt the correct contractual model to expedite AI adoption and achieve its benefits.
What is the change catalyzer?
IT leaders must understand that not letting go of the 2000s IT support model (technology and processes) is slowing down their ability to optimize IT operations and increase customer satisfaction. In this new millennium, the focus needs to be on technology adoption, not on process adoption. The tools and especially IT processes that IT leaders have been purchasing belong to a different era. When IT leaders change what they are buying, they will set in motion a transformation which accelerates AI adoption and consequently will drive exponential benefit to their organizations, and to their risk profile. IT staff costs and IT continuity risk can be dramatically reduced via AIOps adoption powered by an SRE Operational model.
Digitate: Paving the way for an autonomous enterprise
In 2024, Digitate collaborated with Sapio Research to survey 601 IT decision-makers from U.S. organizations with over 1,000 employees, focusing on IT leaders’ automation goals and strategies. According to the results, 26% of companies seem to be moving toward more autonomous operations within the next five years. (To view the full report, click here)
ignio™, Digitate’s SaaS platform that is built on an agentic architecture, is paving the way for this shift. ignio aims to drive IT autonomy, helping enterprises achieve smoother, more efficient, and future-ready IT transformation.
To learn more, feel free to connect with me or the Digitate team.
