Rishi Chohan, U.S. CEO of GFT Technologies – Interview Series

Rishi Chohan, U.S. CEO of GFT Technologies, is a seasoned digital transformation leader with over 20 years of experience across the software and services industry, including roles at Ernst & Young and SoftServe. Since taking the helm in 2025, he has focused on scaling GFT’s AI-driven strategy across the U.S. by strengthening ties with financial institutions, manufacturers, and tech partners while modernizing legacy systems for AI readiness.

GFT Technologies is a global digital transformation and software engineering firm specializing in AI, cloud modernization, and platform innovation for the banking, insurance, and manufacturing sectors. Founded in 1987 and operating in over 20 countries, GFT brings together more than 12,000 professionals. Its work is guided by five core values: Caring, Committed, Collaborative, Courageous, and Creative.

You’ve led transformations at major institutions like EY and SoftServe, but stepping into the U.S. CEO role at GFT during a pivotal AI shift is a unique challenge. What personally drew you to this opportunity—and what excites you most about shaping GFT’s next chapter?

From the very beginning of my conversations with GFT, I realized the company was in a position to attack common industry challenges a lot differently than even the most established digital transformation players. It was clear that the company was a financial services powerhouse, both in terms of its technical expertise and, perhaps even more importantly, its deep domain knowledge. The team I would be working with had knowledge that might even surpass the financial institutions themselves.

As we continued talking, I quickly formed a vision for how I would approach this opportunity to transform financial services firms for their own AI futures, while GFT is simultaneously undergoing its own AI-centric transformation.

Now that I’ve spent a few months working within the organization, I’ve confirmed my initial suspicions: The fact that we sit at the intersection of technical expertise, deep financial knowledge and extensive AI experience puts us in a very unique position to reinvent legacy business models and approaches–either from the ground up or one piece at a time. It’s a choose-your-own-adventure approach to disrupting an industry that’s ripe for disruption, and I’m happy to be a part of it.

GFT is in the midst of a five-year journey to become a fully AI-centric company. Internally, what does that look like so far?

There are four major areas we’re addressing. In broad strokes, those are:

1. Auditing our processes and operations to determine how and where AI can elevate team members.
2. Determining opportunities to capitalize on in the short term, as well as what we need to be building for the long-term. This includes identifying areas where employees can utilize AI in their everyday tasks now, while we’re executing on a more overarching roadmap that influences operations holistically over time.
3. Applying our own proprietary generative AI solution to scale our software development for our clients and get them to market faster. We have already seen productivity gains ranging from 30% all the way up to 90%, depending on the project, as a direct result of implementing this AI to deliver on new services and offerings.
4. Educating our employees through the transition to making sure it’s clear to them where AI can step in and where they can grow with it to support the company’s evolution.

Can you share specific examples or use cases that illustrate the impact of GFT’s generative AI solution, especially in financial services?

A good recent use case I can point to, is a new solution we developed for banks and private capital firms. We built a generative AI assistant that assesses credit risk to inform major lending decisions–at an exponential scale. The new tool automatically pieces together vast amounts of financial data to create credit reports, reducing timelines from hours and even days to mere minutes, while ensuring compliance. By saving time on report creation (we say 40% but that is conservative), credit analysts can now increase their focus on assessing complex risk decisions.

This is solving a major problem considering that in the credit industry, every second counts–but moving too quickly can lead to human error, and a single oversight can impact major lending decisions.

Because it can take days of manual work to compile a risk report, the only way companies have historically been able to move more quickly–without overloading workers and risking mistakes–has been to scale teams. Now, with this new generative AI approach, financial institutions can make lending decisions faster with higher confidence.

Another recent example comes from the largest insurance company in Brazil, which used our proprietary AI tool to identify vulnerabilities in their code and prevent cyber attacks before they happen.

This is critical since large financial institutions are especially vulnerable to hackers – and this insurer in particular was experiencing a number of attacks each day. While they had a large team dedicated to catching and identifying potential leaks before they occurred, due to the sheer amount of vulnerabilities, hackers were still slipping through cracks in their defenses.

GFT’s AI solution has been able to identify anomalies 90% faster than the developer teams could previously. Additionally, once identified, the AI solution is being used to automatically fix the vulnerabilities in the code to prevent attacks, making the process 66% faster than before.

Both of these capabilities together represented efficiency gains of up to 30% in the overall development lifecycle in just 3-4 months.

With your experience leading engagements for top-tier banks like JPMC, Morgan Stanley, and Citibank, how are you tailoring GFT’s AI strategy to meet the hyper-specific needs of U.S. financial institutions?

From my work with top-tier banks, and within several facets of the financial space, I’m clear on the potential that AI represents for financial institutions. The knowledge I bring with me to GFT complements the company’s own 35 years in the financial space.

Over the years, I’ve witnessed first hand the common challenges that arise across the projects I’ve had the privilege of working on, as well as the nuanced pain paints faced by individual companies. Being able to see these macro trends and how they affect both the industry at large and specific companies has given me a very clear grasp of how and where to apply AI. Across the board, challenges such as money laundering, fraud, customer identification and complex credit reports have plagued institutions for years.

For example, GFT is infusing Google Vertex AI into a leading bank to enhance its fraud detection. Despite the technology not typically being used for that purpose, the institution needed a solution that could be easily integrated into its complex systems. To support this request, GFT is helping the bank train Google Vertex on common patterns in order to identify potential fraud and trigger action to prevent it.

Additionally, GFT is working with AWS to build AI-driven solutions for banks. In Singapore, we have built a custom anti-money laundering process driven by AI.

From a big-picture GFT strategy perspective, I’m working to strike the right balance of advancing our own proprietary AI solutions and those we’re building for clients alongside  our long-term tech partners like Google and AWS.

GFT aims to become a global leader in responsible AI. What guardrails or governance frameworks are you putting in place to ensure safety, transparency, and regulatory alignment, particularly in highly regulated sectors?

Different financial institutions follow different regulations; as of now, there isn’t a one-size-fits-all guardrail when it comes to AI. This means that in order to stay compliant and ensure safety for each and every client, we adjust to the particular organization’s rules.

The solutions we provide are easily adaptable. Before launching we make sure we are acquainted with the regulations and rules associated with that specific institution and adjust the solution to comply with their environment. This way there are never any safety or regulatory issues that arise.

In addition to curating our solutions for different companies’ regulatory requirements we also follow industry regulations such as GDPR in Europe.

You’ve been described as a data-driven, action-oriented leader. In practice, how do you foster that culture across such a large organization—especially one undergoing rapid AI transformation?

The first step in fostering a data-driven culture across an organization is ensuring that every member understands the benefit of working in that way.

In order to successfully operate a business, teams need access to organizational data. It gives an inside look into what’s working and what’s not, and can give projections of probable outcomes for different scenarios. Armed with this data it is that much easier to make decisions that are right for your company.

To demonstrate this, it is essential to lead by example and show how data driven decisions can bring meaningful change that benefits everyone in the organization. For example, if sales data shows that conversion rate is low, we know that that is an area that needs attention and can create a strategy to remedy the challenge. Once the beneficial outcomes of a data driven culture is clear it is easier for teams across the organization to seamlessly adopt the practice.

Especially as we undergo a rapid AI transformation, data is essential to understanding how the change is working and where there may be areas for improvement.

Beyond banking, how is GFT applying its AI strategy to other sectors like manufacturing? Are there unique challenges or opportunities in translating financial sector learnings to industrial applications?

In the manufacturing industry GFT has a strong partnership with Google. Together over the past year we have been releasing AI use cases specifically formulated for manufacturers’ factory floors.

Last year, we announced the implementation of Google Cloud’s Manufacturing Data Engine (MDE), which fueled AI capabilities such as visual production line inspection, predictive machine maintenance, and production forecasting. Now, this year, we have unveiled our next set of applications built on Google’s Gemini Models, including the ability to determine the root cause of errors and defects, visual dashboards that enable users to query organization-wide data in natural language and the ability to convert thousands of machine training manuals into avatar-led video demonstrations.

When it comes to translating learnings from the financial sector to industrial applications, it’s less about the industry itself and more about discoveries in the code. In every industry, learnings on code development and software life cycles are important and transferable – the code may create and do different things but certain roadblocks or challenges with software development are universal. We use what we learn in every project whether it be for financial institutions or manufacturers to bring deeper insights into our next project.

With strategic partnerships in place with NVIDIA, AWS, and Google Cloud, what do you see as the next evolution of GFT’s ecosystem approach? Will vertical-specific AI products be co-developed or independently built?

We’ve already begun both co-developing and independently building AI solutions. The manufacturing AI use cases we have released with Google Cloud are just the beginning of our work automating the factory floor. We also soon plan to release financial specific AI use cases that we have developed with AWS for U.S. banks.

Additionally, we are continuously expanding our independently built generative AI solution for software development.

GFT’s five-year strategy includes bold targets: reaching €1.5B in revenue and becoming a recognized AI leader. As you look ahead to 2029, what milestones or signals will tell you that the company is truly on track?

Our two main goalposts that are essential to hit revolve around culture and solutions.

Firstly, we must change both the mindset and hard skills of everyone in the organization so that AI is at the forefront of how we operate. This is not limited to our technical staff, every team member whether they be a developer, a sales rep or a marketer will be completely trained on using our AI solutions.

Second, we are measuring success by the high value-add services that we are delivering to our customers. In the next five years we hope to see the percentage of projects that have AI embedded into both the services and products we’re delivering skyrocket.

We’ve already seen significant progress on both fronts, with a large portion of our staff already trained and using AI internally, as well as an increasing AI element in the projects we are engaging in. These baseline goals are essential to set a strong foundation. At GFT we know that AI is going to continue to evolve in coming years and the only way to stay ahead of it is to prepare now.

Finally, now that you’ve had a few months in the role—what’s surprised you most about GFT’s culture or capabilities? And what’s one misconception people still have about enterprise AI transformation that you’d like to correct?

I can’t emphasize enough the depth of financial services and tech expertise that co-exist simultaneously at GFT. It puts us in a position to not just execute on ideas that organizations come to us with, but guide them based on our experience working with banks across the globe. We lay out long-term visions that  are quite often a lot bigger–with a lot more revenue generating potential–than what they would have come up with on their own. As I continue to learn of past and current work GFT has done across regions, I realize there are few spaces in the industry that GFT has not touched on.

I’d say that a misconception about enterprise AI transformation is that it’s all hype. That’s something that organizations often like to tell themselves to buy themselves time to figure it out. The sooner that organizations accept that AI is here to stay and will change how they do everything–in a good way–the sooner they can begin realizing its potential in both very small and very big ways.

Thank you for the great interview, readers who wish to learn more should visit GFT Technologies.