Hallucination is not an option when AI meets the real world: Dr Burkhard Boeckem, CTO, Hexagon

When Dr Burkhard Boeckem, Chief Technology Officer at Hexagon, talks about artificial intelligence, he is not talking about prompts, copilots, or abstract productivity gains. He is talking about machines that operate in the real world, machines that know where they are, understand their surroundings, and make decisions that cannot afford to be wrong.

“Hallucination is not an option,” Boeckem says. “If you deploy AI into physical reality, the bar needs to be so much higher.”

It is a deceptively simple statement, but it cuts to the heart of a widening fault line in enterprise AI. As generative AI dominates headlines, Hexagon is operating in a different domain altogether, one where intelligence must be grounded in physics, geometry, and spatial truth. For Boeckem, this is not the future of AI. It is the present.

Why measurement still Matters in an AI-first world

At Hexagon, AI does not begin with software. It begins with measurement. “Foremost, we are a measurement company,” Boeckem says. “Precision measurement and positioning, that is our foundation.”

That foundation spans micrometre-level accuracy in manufacturing, millimetre-level precision in geospatial systems, and real-time perception in autonomous environments. Sensors, LiDAR, cameras, radar, scanners, form the starting point. But measurement alone is not the destination.

“What customers do with our sensors is create 3D environments,” he explains. “Ultimately, they create digital twins.”

These digital twins are not static visual models. They are dimensionally accurate, continuously updated representations of the physical world, cities, factories, mines, infrastructure, even human anatomy. Managing the sheer volume of data involved requires seamless movement between edge and cloud, and tight integration between hardware and software.

Once the physical world becomes machine-readable, intelligence can be layered on top.

“That’s where spatial intelligence comes in,” Boeckem says. “You can classify, segment, and understand objects and environments. And once you have that understanding, you can improve operations, productivity, planning, and safety.”

What truly differentiates Hexagon, however, is what happens next.

When AI leaves the cloud, safety becomes non-negotiable

For Boeckem, the most consequential AI applications are not advisory. They are autonomous. “In industrial environments, AI doesn’t just recommend,” he says. “It acts.”

That shift, from insight to action, raises the stakes dramatically. Autonomous systems operate in safety-critical environments where failure can result in physical damage, financial loss, or human harm.

“When generative AI went mainstream in 2022, it was exciting,” Boeckem says. “But professional environments need AI that is grounded in reality. These systems must always know where they are, what obstacles exist, and what the consequences of an action might be.”

Hexagon has been designing for this reality for years. In mining, the company enables fully autonomous haulage systems. In robotics, it is working on humanoids and industrial autonomous machines that must coexist with humans.

“If you have robots working alongside people, regulations matter,” Boeckem says. “You must design safety into the system from day one. You must ask: what happens if something fails? How do we prevent accidents?”

This is what Boeckem calls physical AI: intelligence that is not just informed by data, but constrained by the laws of the physical world.

The digital twin fallacy and what enterprises miss

Despite the growing popularity of digital twins, many enterprises struggle to make them operational. According to Boeckem, the problem is not ambition, but misunderstanding.

“A digital twin must be fit for purpose,” he says. “And above all, it must be dimensionally accurate.” Accuracy is non-negotiable. A flood simulation requires a watertight model. Urban planning demands precise representations of sunlight, shadows, and surroundings. Aesthetic simulations require photorealistic textures and material properties.

At the most complex end of the spectrum, Hexagon models human faces. “A human face is not static,” Boeckem explains. “It’s soft-body material. When you smile, when you’re angry, when you’re sad, it changes. If you want to do diagnosis or therapy, you have to account for that.”

Beyond accuracy, digital twins must be evergreen, continuously updated to reflect reality. Context completes the picture. Without it, even the most detailed model remains academically impressive but operationally useless.

India as Hexagon’s cross-industry innovation engine

For Hexagon, India is not an offshore development centre. It is a strategic nerve centre. “India R&D is super important for us,” Boeckem says. “It sits at the intersection of different divisions and enables cross-pollination.”

Hexagon serves 28 industries globally, but the underlying technologies remain consistent. Whether mapping the Earth’s surface or modelling a human face, the same foundational capabilities, measurement, digital twins, spatial intelligence, apply.

“All our business areas have R&D teams here,” Boeckem says. “And part of my own organisation, the Innovation Hub, has a presence in India as well.”

This Innovation Hub acts as the connective tissue between Hexagon’s decentralised global R&D teams, focusing on core technologies that feed into products worldwide. The ability to bring diverse teams and disciplines together under one roof in Hyderabad, Boeckem says, is “phenomenal.”

Engineering industry-firsts at industrial scale

Hexagon’s ambition is backed by sustained investment. The company reinvests around 15 percent of its revenue into R&D and releases close to 500 new products or major updates every year.

Among its recent industry-first innovations is an ultra-compact airborne mapping system combining LiDAR and high-resolution cameras on small aircraft. “What makes it unique is that the pilot can operate the mapping system directly during flight,” Boeckem says. “That workflow was developed by our India R&D team.”

Another breakthrough is MyMO, a compact asset health monitoring system that uses radar and imaging to assess the structural integrity of bridges and buildings remotely. 

“Asset health used to be very domain-expertise-heavy,” Boeckem notes. “Now it’s standardised.” Once asset health data flows into a digital twin, AI can identify risks, predict failures, and prioritise interventions at scale. “These are just two examples,” Boeckem says. “But they show how we change industries.”

Competing with hyperscalers by grounding AI in physics

As hyperscalers and AI-native players push deeper into industrial intelligence, Hexagon’s strategy is not confrontation, it is collaboration. “We have very strong partnerships with NVIDIA, Microsoft, AWS, OpenAI, and Anthropic,” Boeckem says.

Hexagon’s humanoid robot, Aeon, runs NVIDIA’s physical AI and compute both in its body and head. Hyperscalers provide the cloud and AI compute required to process massive geospatial datasets.

Yet Boeckem is clear about where Hexagon’s advantage lies. “What differentiates us is grounding AI in reality,” he says. “The more AI advances, the more it depends on accurate, dimensionally correct data.”

Internally, Hexagon develops more than 20 domain-specific foundation models every year; tailored to tasks such as point-cloud classification and autonomous perception. “That domain depth is very hard to replicate,” Boeckem says.

From autonomous decisions to autonomous operations

Hexagon’s end goal is not smarter analytics dashboards. It is autonomy at scale. “We enable companies to drive their autonomous future,” Boeckem says. “To make better decisions and build self-sustaining systems.”

In manufacturing, that vision translates into lights-off factories where shop floors operate autonomously. In infrastructure and cities, it means predictive maintenance and resilient systems. In robotics, it means machines that can work alongside humans without compromise.

“This is the age of intelligence,” Boeckem says. “And physical AI is where that intelligence becomes real.” For Hexagon, the future of AI is not virtual. It is measurable, grounded, and unmistakably physical.