C-Suite Perspectives On AI: Gino Ussi Of Elsevier On Where to Use AI and Where to Rely Only on Humans

An Interview With Kieran Powell

Accelerate synthesis planning for novel compounds/de novo design.

As artificial intelligence (AI) continues to advance and integrate into various aspects of business, decision-makers at the highest levels face the complex task of determining where AI can be most effectively utilized and where the human touch remains irreplaceable. This series seeks to explore the nuanced decisions made by C-Suite executives regarding the implementation of AI in their operations. As part of this series, we had the pleasure of interviewing Gino Ussi.

Gino is President of Elsevier’s global corporate markets, comprising Elsevier’s Life Sciences, Engineering and Global Pharma businesses. Gino has also served as a member of the United Nations Economic Commission for Europe team of specialists for Internet and e-Commerce Development. He has an MSc in Change Management from Oxford Said Business school, a DipBA in Strategy from Aston Business School and Marketing Communications from Witwatersrand.

Thank you so much for your time! I know that you are a very busy person. Our readers would love to “get to know you” a bit better. Can you tell us a bit about your ‘backstory’ and how you got started?

I grew up in South Africa, the son of an Italian father and Australian mother. My father was a miner who worked in the gold mines so I grew up in a small village in the middle of nowhere. I left South Africa in 1983 and moved to England where I started my career working for Europe’s largest contract publisher. Later in my career, I started a company called the World Markets Research Center, which provided information on foreign direct investment for investors who were interested in expanding their operations into other markets. This was a pivotal time in my career and it allowed me to step outside of my comfort zone and learn new things. During that period, my business partners and I developed a political, financial and economic risk model for foreign investment that was updated every day. We did an analysis of the news that happened over the last 24 hours and it went out as the morning briefing. The business grew exponentially and so did our client base. Shortly after, I sold the business to a firm called Global Insight and was named president.

There were multiple factors that contributed to the success of the business, but I believe the innovative deployment of new internet technologies was the driving factor. And now we’re seeing a new disrupter transforming industries — generative AI — which will continue to accelerate change and deliver new ways of working and accessing information like we’ve never seen before. The potential societal benefits to be derived from new generative AI technologies are likely, in my opinion, to significantly surpass those brought about by the introduction of the Internet technologies in the 1990s.

I joined Elsevier in 2012 and currently lead the global business segment that provides advanced solutions and services to organizations in R&D-intensive industries such as pharmaceuticals, biotech and chemicals. Simply put, we operate at the intersection of data, technology, and applied science to deliver trusted solutions that drive innovation. I’m proud of the work we do and the trust we’ve built with R&D leaders across a wide range of industries who rely on Elsevier for our combination of unparalleled peer-reviewed content, extensive curated data sets, and sophisticated analytics that drive critical insights and decision-making across the R&D cycle. We are also working closely with our R&D customers to develop and hone our most advanced AI solutions. By engaging in meaningful conversations with our users, conducting thorough testing, and maintaining our focus on responsible AI practices, we can continue to develop innovative solutions that help shape the future of research and health outcomes worldwide.

It has been said that our mistakes can be our greatest teachers. Can you share a story about the funniest mistake you made when you were first starting? Can you tell us what lesson you learned from that?

I’m going to take you way back to the 90’s. One mistake I made earlier in my career was underestimating the infrastructure and overall costs of building the right systems and capabilities to fully leverage the impact of new technologies such as the Internet. During that time, I assumed it would be easy and inexpensive to monetize key solutions using a free service like the Internet but I was wrong. I quickly learned how challenging and costly it can be to develop and implement the right software and hardware, and of course create value for our customers. It was certainly a time where business leaders and entrepreneurs could learn, make big bets and move fast.

Are you working on any exciting new projects now? How do you think that will help people?

At Elsevier, everything we do is rooted in trusted, quality, verified information. Our products and solutions draw from the millions of accurate, verifiable and up-to-date information including peer-reviewed articles and abstracts from scientific journals, medical books and evidence-based clinical overviews. Having trusted content is critical to the research and healthcare communities that we serve. If we take life sciences as an example, trusted content is essential for drug discovery. We complement that with predictive models using AI that help our customers derive the right insights, summarize and synthesize data more effectively.

Elsevier’s peer-reviewed content represents 20% of global research output. As part of RELX, the company also has access to 10,000 technologists who are experts in their domain. The combination of rich datasets, technology infrastructure, and knowledge of how to use next generation innovation allows Elsevier to work with organizations to empower scientific discovery. By starting with data and domain-specific knowledge, Elsevier helps customers build intelligent Gen AI applications that help them access trusted information faster for better decision making.

Thank you for that. Let’s now shift to the central focus of our discussion. In your experience, what have been the most challenging aspects of integrating AI into your business operations, and how have you balanced these with the need to preserve human-centric roles?

As a global leader in scientific information and data analytics, Elsevier has been using artificial intelligence (AI) for more than a decade to develop intelligent decision tools that enable researchers to apply trusted knowledge to scientific problems. New generative AI (GAI) technologies offer the potential to transform R&D and accelerate breakthroughs.

Some of the challenges we have faced in integrating the latest AI technologies into our business operations are those that all companies are grappling with. Of paramount importance is ensuring the highest levels of privacy, security and compliance.

To deliver on the potential of GAI, a combination of high-quality, domain-specific data with advanced data science skills is critical. We employ thousands of subject matter experts across Elsevier — MDs, PhDs, RNs, MPH and other experts — in the review of our products and in the output created by our AI solutions.

Can you share a specific instance where AI initially seemed like the optimal solution but ultimately proved less effective than human intervention? What did this experience teach you about the limitations of AI in your field?

I can’t point to a specific instance, but I will say that a critical part of our generative AI development is ensuring human oversight stays at the forefront. There are well documented limitations to AI, including hallucinations that can lead to faulty, biased, or legally and scientifically dangerous results.

Given that our customers operate in sensitive areas like research and life sciences, we place great emphasis on being responsible stewards of personal and proprietary information. Part of our ethos is ensuring that we create transparent and ethical technology that supports human decision-making and is explainable to our customers, auditors, regulators, and policymakers.

How do you navigate the ethical implications of implementing AI in your company, especially concerning potential job displacement and ensuring ethical AI usage?

Using AI has long been a part of the Elsevier fabric, and we are guided by our Responsible AI and Privacy Principles as we deliver the right outcomes for our customers as well as society at large. The principles underpin all AI development, machine learning and data science projects so that we hold ourselves accountable to consider the real-world impact of our solutions, aim to prevent bias, can explain how our solutions work, maintain human oversight and protect privacy.

A critical part of our AI development is ensuring human oversight stays at the forefront. AI serves as a copilot to augment human researchers’ skills — cutting through billions of possibilities so researchers can prioritize the most feasible that are supported by underlying data and evidence. It is important that Elsevier AI tools continue to support the discovery and application of trusted knowledge safely and effectively.

Could you describe a successful instance in your company where AI and human skills were synergistically combined to achieve a result that neither could have accomplished alone?

When combining generative AI with trusted content, Elsevier can make a real difference in the research and healthcare communities and contribute to society. Our customers make high value decisions and need to trust the information they are receiving.

In the last year and a half, we have actively engaged our customers in the product development process which allows us to deliver tools that address their challenges. After robust testing and input from our customers, we have launched four cutting edge AI solutions: Scopus AI and SciBite Chat for researchers; ClinicalKey AI for clinicians; and Sherpath AI for nursing faculty and students. This fast pace of innovation wouldn’t have been possible without the knowledge and work of our top experts, including thousands of technologists working around the globe, and the invaluable support of our strategic partners and customers.

Based on your experience and success, what are the “5 Things To Keep in Mind When Deciding Where to Use AI and Where to Rely Only on Humans, and Why?” How have these 5 things impacted your work or your career?

This is an interesting question. In my view, it shouldn’t be one or the other. As we have already seen, Generative AI can advance work and drive efficiencies across industries. For example, it can help researchers in disciplines such as medicine, climate science and green technology to address common failure points in existing research workflows. I believe AI will accelerate the pace of research and help teams surface connections that humans might have missed, while maintaining certain standards that are required in highly regulated industries.

If we look at R&D as a use case, here are some of the ways AI can help in drug development and small molecule discovery:

• Lead identification and optimization phases.
• Molecule design, planning chemical syntheses and predictive retrosynthesis.
• Predict/understand structure-activity relationships.
• Make accurate ADME and toxicity predictions.
• Accelerate synthesis planning for novel compounds/de novo design.
• Improve route optimization for known compounds.
• Predicting how drugs will behave in patients.

Looking towards the future, in which areas of your business do you foresee AI making the most significant impact, and conversely, in which areas do you believe a human touch will remain indispensable?

I believe the biggest impact will be in drug discovery and sustainability. For example, delivering better and faster insights for scientific discovery, helping cosmetics companies find alternate ways of testing that does not involve animals, identifying sustainable approaches for energy, and much more. Without question, AI will continue to help drive greater effectiveness and speed in the way we approach and accomplish tasks — from the simplest to the most complex.

You are a person of great influence. If you could start a movement that would bring the most amount of good to the most amount of people, what would that be? You never know what your idea can trigger. :-)

I’m always startled and saddened by the number of children in this world who grow up with parents who didn’t have the skills or knowledge to be the kind of parent they wanted to be. I would like to start a movement that is centered on helping families by giving them the information, tools and support they need to raise happy, successful children.

How can our readers further follow your work online?

One of the best ways to stay connected and follow my work and our collective contributions as Elsevier is via LinkedIn. I appreciate the opportunity to share my thoughts for this article.

This was very inspiring. Thank you so much for joining us!

About The Interviewer: Kieran Powell is the EVP of Channel V Media a New York City Public Relations agency with a global network of agency partners in over 30 countries. Kieran has advised more than 150 companies in the Technology, B2B, Retail and Financial sectors. Prior to taking over business operations at Channel V Media, Kieran held roles at Merrill Lynch, PwC and Ernst & Young. Get in touch with Kieran to discuss how marketing and public relations can be leveraged to achieve concrete business goals.