While many companies are caught up in the AI hype cycle, ABB, an industrial robot supplier and manufacturer, has been building and implementing practical AI solutions for nearly a decade.
In an interview with AIM, Sami Atiya, president of the robotics and discrete automation at ABB, expressed how the company has taken a measured, value-driven approach to AI innovation, which is delivering results across multiple industries.
“We at ABB had our first research done in AI more than a decade ago, in 2014. It’s already implemented in many of the systems we use today,” noted Atiya. This long-term perspective has helped ABB distinguish between AI hype and genuine technological maturity.
This, according to him, is a critical approach considering the cycles of inflated expectations and subsequent “AI winters” that have shaped technological development over the past few years.
Different Approach to AI Implementation
Rather than creating centralised AI teams or pursuing grand projects, ABB has adopted a distributed, customer-centric approach. “What we learned is we don’t drive technology from the top of central needs. We drive it from customer needs,” Atiya explained.
The company maintains an AI Council that coordinates activities, manages an AI repository, and oversees education initiatives while allowing individual teams to develop solutions based on specific customer requirements.
This approach has allowed ABB to categorise and track projects across the company, distinguishing between implemented solutions, pipeline developments, and exploratory ideas. This method, Atiya said, not only ensures that promising concepts are nurtured but also avoids the pitfall of investing in ideas that may not materialise.
Over the last decade, ABB has expanded its AI portfolio to include over 250 projects, many of which are already delivering tangible results. “Most of these projects here are available for purchase today,” Atiya said.
Real-World AI Applications
One of ABB’s most impressive achievements is in robotic vision and navigation. The company has developed AI systems that allow robots to recognise and handle objects they’ve never encountered before. “What our research has done is that we now have a neural network that can recognise the shape of the object that it has not seen before,” explained Atiya.
Another groundbreaking implementation is in factory navigation. Using the Visual SLAM navigation technology, powered by AI and 3D visual detection, robots can now navigate complex factory environments without requiring physical guides or markers.
“The robot actually goes around, figures out where it is, and then starts creating a map… You put another robot in, they talk to each other, and they learn,” Atiya described this advancement.
AI’s Role in Sustainability and Workforce Evolution
Sustainability is a cornerstone of ABB’s AI strategy. This was highlighted during a panel discussion led by Sara Larsson, CEO at the Swedish Chamber of Commerce India, featuring leading AI experts like Khushaal Popli, program director, IIT Bombay; Kishan Sreenath, VP, Powertrain, VolvoGroup; and Kaushik Dey, head of research, Ericsson.
Panel discussion at ABB, Bengaluru campus. (From left to right) Sara Larsson, Kaushik Dey, Kishan Sreenath, Khushaal Popli, Sami Atiya, and Subrata Karmakar.
AI-powered solutions like building analysers optimise energy consumption by integrating weather forecasts, operational data, and energy patterns. These efforts not only improve efficiency but also support global sustainability goals.
As industries evolve, so too must their workforces. ABB invests significantly in upskilling its employees by combining AI expertise with engineering knowledge.
Atiya also shared insights into ABB’s hackathons and training programs, including a recent initiative in India that trained 2,000 employees on AI on the same day and generated over 200 new AI use cases.
He explained this as a compact way of reinforcing and energising the teams. “It’s not just about hiring AI experts; it’s about expanding the capabilities of our existing teams,” he remarked.
ABB’s Strategic Upskilling and Recruitment
ABB’s leadership in AI extends beyond technological advancements to strategic talent acquisition and workforce development. With over 10,000 employees in India, ABB leverages the country’s exceptional talent pool across engineering and software domains.
According to Atiya, ABB recruits top-notch professionals while maintaining a low attrition rate, owing to its strong reputation and focus on employee growth and education. “We like to keep our employees,” Atiya said.
However, the company’s strategy isn’t limited to external hiring; upskilling its existing workforce is a key priority. He emphasised the importance of blending AI expertise with engineering disciplines like mechatronics to foster innovation.
This approach ensures ABB’s teams are equipped with both technical knowledge and domain-specific expertise, which is critical for solving industry challenges. “It’s not about hiring AI experts alone; it’s about expanding the capabilities of our own people,” Atiya highlighted.
By cultivating multidisciplinary teams and prioritising lifelong learning, ABB is building a workforce ready to lead industrial transformation. This reaffirms its commitment to people as its greatest strength.
In addition, Atiya also emphasised at this year’s World Economic Forum in Davos, “Like robotics, AI will lead to new jobs and change the way we work. We must inspire innovation and emphasise the importance of learning and upskilling to realise its benefits.”
Synthetic Data and AI Limitations
ABB’s success is built on collaboration. To foster innovation, it works with startups, universities, and technology leaders. Partnerships like its acquisition of Sevensense for advanced robot navigation and ongoing collaborations with IIT Bombay are vital to scaling breakthroughs.
Atiya was candid about the challenges of AI, particularly the risks of bias and data misalignment.
He stressed the importance of synthetic data in addressing the shortage of real-world training data but warned of the risks of amplifying existing biases if quality controls are inadequate.
He also acknowledged that while generative AI and LLMs have potential, they face limitations.
The Future of Human-Machine Collaboration
Atiya sees natural language interaction as the next frontier for human-machine collaboration. ABB is pioneering systems that enable robots to understand complex verbal commands, such as arranging objects based on human instructions.
“In the past, we had to learn the language of machines. In the future, machines will learn ours,” he noted. This focus on human-centric AI aligns with ABB’s broader mission of enhancing human capabilities, not replacing them.
