Women in STEM: Lessons on AI, Confidence and Representation

In June, I attended the Women in TechWorks Engineering Intelligently event in Cambridge. It brought together leaders from across technology, semiconductors, engineering, academia and government to discuss the biggest challenges and opportunities facing women in STEM and the wider industry. I then published an article about why women leave technology based on the event.

While the agenda covered topics ranging from AI and engineering leadership to mentoring, innovation and inclusion, a common thread ran throughout the day:

Technology is evolving rapidly, but people remain at the centre of progress.

The future of engineering is increasingly human

One of the most striking observations came from Arm, which highlighted how dramatically engineering complexity has changed.

In 1961, a chip containing four transistors could be designed by a single engineer. Today, leading-edge semiconductor devices contain tens of billions of transistors and require thousands of engineers working together.

As technology becomes more complex, success depends less on individual brilliance and more on collaboration.

"Great things in business are never done by one person. They're done by a team of people."

Relationships, communication, trust and collaboration are becoming increasingly important engineering skills.

As one speaker noted:

"Relationships are how complex results get done."

AI in engineering: a multiplier, not a replacement

Artificial intelligence featured heavily throughout the event. From engineering knowledge management and design automation to simulation acceleration and decision support, speakers demonstrated how AI is becoming embedded in engineering workflows.

One presentation described AI as an engineer's "second brain." The goal is not to replace expertise but to amplify it.

Several speakers discussed systems that combine curated organisational knowledge, project context, meeting notes and AI agents to help teams make better decisions and reduce time spent searching for information.

This mirrors what we see at yieldHUB every day. Semiconductor companies generate enormous volumes of test data, and the teams that get ahead are the ones that centralize it and let engineers spend their time on analysis rather than searching. AI does not change that principle. It accelerates it.

The message was clear: technology will continue to evolve, but human potential remains the multiplier. The engineers and leaders who learn how to work effectively alongside AI will have a significant advantage.

Confidence comes after action

One of the most memorable themes of the day centred on confidence.

Many people think confidence comes first and action follows. The speakers challenged that idea. Confidence often arrives after action. After taking the step. After asking the question. After speaking up. After trying something new.

Several practical pieces of advice stood out:

• Say what you think in the first five minutes.
• Sit at the table.
• Know your value and bring it with you.
• Progress rarely happens when everything feels comfortable.

Another important distinction emerged between mentoring, coaching and sponsorship. Mentors provide guidance and advice. Coaches help people make decisions. Sponsors actively advocate for people and create opportunities.

The advice was simple: get a mentor, find a sponsor and become a mentor for someone else.

Representation is infrastructure

A significant portion of the event focused on the challenge of attracting and retaining women in technology.

One statement particularly resonated:

"You can't be what you can't see."

Another speaker expanded on this idea:

"Representation is infrastructure."

Representation is not simply a diversity metric. It creates visibility, possibility and pathways for future generations.

The gender gap is systemic and begins early. The data presented also debunked a myth: caregiving is not why women leave technology. Only 3% cited it. The real drivers are organisational. I covered the full research in Why Women Leave Tech: 2026 Retention Data Says It's Not Caregiving.

This is why representation matters so much. Visible role models do more than inspire. They demonstrate what is possible. They help young people imagine themselves in careers, leadership positions and industries they may never have previously considered.

The future leadership of technology companies is being shaped long before people reach management level. In many cases, it begins in schools, universities and the experiences that influence career choices from an early age.

Innovation requires learning fast

Several sessions focused on product development, innovation and decision-making. A recurring message was that successful innovation is rarely about having perfect information. Instead, it is about learning quickly.

The advice was consistent:

• Focus on solving user problems.
• Validate assumptions early.
• Learn as quickly and as cheaply as possible.
• Gather evidence before making large investments.
• Be willing to adapt.

One speaker summarised the mindset with a memorable phrase:

"Pivot like it's 1999."

Innovation requires experimentation, flexibility and a willingness to challenge existing assumptions. Customers ultimately determine product-market fit, not internal teams. The organisations that learn fastest often win.

Careers are not linear

Another important theme throughout the day was career development. Many attendees shared stories of unexpected career paths, lateral moves and opportunities that emerged from taking chances rather than following a predefined route.

Skills are transferable. Careers do not need to be linear.

People were encouraged to stop waiting until they met every requirement before pursuing opportunities. Instead, the emphasis was on growth, adaptability and continuous learning.

As technology continues to evolve, the ability to unlearn, adapt and relearn may become one of the most valuable skills any professional can develop.

Building better for those who follow

One of the final questions posed during the event stayed with me long after the sessions ended:

"How do we build better for ourselves and for those who follow?"

It is a question that applies equally to technology, organisations and careers. Whether discussing AI, leadership, innovation or inclusion, the answer seemed remarkably consistent.

Invest in people. Create environments where people can contribute. Recognise talent. Share knowledge. Build communities.

And remember that technology alone does not create progress. People do.

Events like Women in TechWorks serve as an important reminder that the future of technology will be shaped not only by the systems we build, but by the people we empower to build them.

Key takeaways

• Engineering has shifted from individual work to collaboration at scale: a 1961 chip with four transistors needed one engineer; today's devices with tens of billions need thousands.
• AI is becoming an engineering multiplier, a "second brain" that amplifies expertise rather than replacing it.
• Confidence follows action, not the other way around.
• Women leave technology mainly for lack of advancement, recognition and sponsorship, not caregiving. Representation is infrastructure.
• Careers are not linear, and the organisations that learn fastest often win.

About the author

Gillian O'Donnell

Gillian is part of the team at yieldHUB, where she works on helping semiconductor companies turn test data into higher yield. She writes about engineering, data and building a stronger, more inclusive technology community.