Bastien Parizot, senior vice-president, global business services and artificial intelligence (AI) at hygiene and consumer health brands company Reckitt, remains level-headed when it comes to the latest developments in technology. For him, fear of missing out is one of the enemies of AI adoption.
“I think there is a lot changing in the world of AI outside,” says Parizot.
Rather than chasing all of the new shiny tech, he believes IT and business leaders should change the way people work to deploy AI at scale across their organisations.
“I don’t like the words ‘AI strategy’ because we only have one strategy, which is a business one,” says Parizot. “We believe we have an AI approach which enables the business strategy.”
Given the pace of change across the tech landscape, particularly in terms of how quickly AI is evolving, he says a company like Reckitt – which owns brands like Cillit Bang, Durex, Dettol and Nurofen – is not concerned about having access to the latest AI. Instead, he says: “Our business is actually to make sure we put better health in the hands of consumers every day.
“AI should be an enabler to help people do their jobs better,” says Parizot. “We shouldn’t be chasing the latest models, otherwise, I would have shifted through maybe eight models in the past two years. The reality is that we bring value by having AI enabling our core businesses and the processes within the enterprise.”
He says the goal of enterprise AI is to deliver business value. This means moving beyond testing and piloting artificial intelligence and delivering AI projects that scale.
AI in R&D
In May, Parizot, along with chief research and development officer Angela Naef, gave a presentation showing digital science at the company. Among the digital technologies presented was a generative AI tool called WriteItt, a good practice (GxP)-compliant AI platform for document drafting, literature search, and protocol generation.
GxP is a framework and guidance for life science and healthcare. “Validating our system as GxP-compliant ensures further robustness, repeatability and continuous control with strong data integrity and high product quality at the centre,” says Parizot.
Rather than building WriteItt using a generic AI tool layered onto the business, he says it was co-developed with the respective teams in R&D and designed around process reinvention of real workflows.
“Much of the discussion around AI focuses on the technology and performance of large language models,” says Parizot. “Our effort has been on putting AI to work by codifying the tacit knowledge of our teams into AI applications.”
It also embeds context around market categories and Reckitt-specific information. “Applying this approach at scale and consistently across all teams is where we believe AI makes a real difference in driving our winning playbook,” he says.
Looking at how WriteItt works in industrial trials, Parizot says: “Every time we scale a product from the labs to the factory, teams must prepare, review and approve detailed industrial trial reports across category teams, product development teams, quality and supply.
“We run more than 250 of these trials each year across brands, including Lysol and Vanish. With WriteItt, drafting and reviewing become significantly faster – up to eight times faster – which means our teams are spending far fewer hours creating documents and much more time on advancing innovation.”
WriteItt is one of many AI projects helping to support the business. In fact, Reckitt started embedding AI into a transformation that began in the summer of 2024. The company worked with Boston Consulting Group (BCG) and its technology arm, BCG X, on a programme that has enabled Reckitt to modernise key parts of its business.
From a technology perspective, Reckitt has implemented an enterprise-wide AI platform it calls Trinity AI, which brings together different datasets and types of databases as well as AI models, all accessible via managed application programming interfaces.
According to a BCG LinkedIn post, hundreds of teams are using custom AI tools and 40% of employee time has been freed for higher-value work.
In the company’s latest financial results, filed at the end of July 2026, chief financial officer Shannon Eisenhard was asked about the company’s AI investment and IT costs. She said Reckitt was very focused on driving AI across the company.
“We view it as something that’s not only going to enable us to drive productivity, which we’ve talked a lot about, but we also view it as a tool that’s going to help us drive top-line growth, and so we’re very focused on making sure that we’re expanding and focusing on both sides of the equation.”
Looking specifically at token cost, which correlates to how much AI workloads actually cost the business, she said: “We just reviewed it and it’s very small today. We’re assuming it will grow quite rapidly, but even assuming that rapid growth, we don’t see it as something that we’re particularly concerned about at this point in time.”
She said Reckitt is investing heavily in building internal models and capabilities to deliver productivity as well as top-line growth.
An iterative journey
Parizot describes the company’s experience of AI as “a continuous learning journey”. It has used AI to create more content, but he says this may not be how the technology is used a year from now.
While there is no fear of missing out, he says: “We are constantly reassessing the complete return on investment of what we’re doing by domain.”
Reckitt relies on its technology partners to help it build the technology to achieve favourable business outcomes, but Parizot says the key to a successful business outcome is not linked to a particular technology or technology partner.
“It’s our ability to change the ways we work, our ability to bring a consistent way of doing things so that we are being more effective and can change how the business operates,” he says.
For Parizot, regardless of the technology, data and knowledge management codifies the know-how people have and helps everyone across the business access that knowledge.
