TE Connectivity, a global leader in connectivity and sensor solutions, powers innovation across industries — from automotive and industrial to medical technology, data communications, and aerospace. With operations in over 140 countries and annual revenues exceeding $16 billion, TE serves as a backbone for products and systems that are integral to modern life.

At the heart of this transformation is the company’s focus on harnessing data and artificial intelligence (AI) to drive innovation, efficiency, and value creation.

In this first installment of a two-part series, Elena Alikhachkina, Chief Data and AI Officer at TE Connectivity, speaks with Clyde Gillard, North American AI GTM Leader at HPE, about her journey, the company’s approach to unifying its data, and how TE is positioning itself for AI-enabled growth.

Alikhachkina has been in the data, analytics, and now AI space for almost 25 years. She started in consulting, working with companies in Europe. Moving to the U.S., her first role was with The Wall Street Journal during its early digital transformation.

Her subsequent roles in healthcare — at Johnson & Johnson, Glaxo, and Roche — and now manufacturing have given her a unique vantage point on the pace and nature of data transformation across industries.

“Manufacturing may be a little bit behind healthcare and digital industries, but that gives me perspective on how industries are moving and the similar challenges they face,” Alikhachkina notes.

One data: Breaking down silos to power AI

When discussing TE Connectivity’s data strategy, Alikhachkina emphasizes the inseparability of data and AI: “Data and AI are like twins — you cannot separate them.”

Like many large global enterprises, TE Connectivity has accumulated a range of systems through organic growth and acquisitions. This has led to siloed data repositories that can slow innovation.

To address this, the company launched its “One Data” initiative, a strategic shift from system-centric to consumption-centric data management.

“Previously, data was focused on a system. Now, we’ve flipped the model and said: What are the consumption needs? Whether it’s business intelligence, data science, AI models, or digital applications, we are making data accessible and usable across the enterprise,” Alikhachkina explains.

She also points out that the future of AI will introduce new types of “consumers” — AI engines themselves — that will need clean, unified data to operate effectively.

Balancing cloud and on-prem: A hybrid approach

On the topic of infrastructure strategy, Alikhachkina shares TE’s balanced approach to leveraging cloud scalability while maintaining on-premises systems where needed: “For scalability, we’re all going to be in the cloud. But it doesn’t mean one cloud — it’s a multi-cloud approach. On-premises is still going to stay in many areas, particularly in product development and engineering, where we deal with sensitive customer IP.”

This hybrid approach ensures flexibility and security while enabling the company to modernize without disrupting ongoing operations.

The evolving role of the CDO

Alikhachkina also reflects on how the Chief Data Officer role has evolved from one focused primarily on governance to one that drives value through analytics and AI.

“My journey started from analytics and value creation. In my first CDO-type role at Johnson & Johnson, we were enabling advanced analytics and quickly realized we couldn’t do it without proper data management,” she says.

That insight has shaped her belief that governance and value creation must go hand in hand. At TE Connectivity, this philosophy has led to pioneering policies, including a framework for “AI in Production.”

“Data scientists are innovators, but they’re not trained in production processes. We needed a policy that ensures risk assessment, support, and escalation paths when AI models go live. We’re one of the first companies to champion such a policy,” Alikhachkina states.

AI use cases: Balancing quick wins and strategic impact

For TE Connectivity, AI use cases range from commercial and customer service applications to engineering-driven innovation. While quick wins in commercial functions provide immediate value, the most significant opportunities — and challenges — lie in using AI to accelerate product development and enhance sustainability.

“Using AI in engineering to make products faster to market, more desired by customers, and more sustainable — that’s where the biggest opportunities are,” Alikhachkina explains.

In 2024, TE introduced tools that allow engineers to summarize product information from extensive PDF documentation, enabling faster innovation while maintaining strict compliance with IP and regulatory requirements.

Alikhachkina also emphasizes the importance of leveraging embedded AI capabilities from partners like SAP, Salesforce, and Microsoft: “We don’t need to build everything. For example, SAP has launched over 400 AI products and agents — we should be using those. The same goes for Salesforce and Microsoft’s Copilot.”

As TE Connectivity continues its AI transformation, the company’s focus remains clear: unify data, create robust governance frameworks, and strategically deploy AI where it delivers the most value.

CDO Magazine appreciates Elena Alikhachkina for sharing her insights with our global community.