Product, Service & Design Innovation
Could AI Hold the Key for Brands Struggling to Unlock the Ambition-Action Conundrum?

A survey carried out by Smurfit Kappa earlier this year confirmed what we already suspected: Despite most companies showing increased ambition when it comes to sustainability, there is still a big gap between renewed levels of ambition and the action needed to turn the dial.

Among the 440 senior managers surveyed, half claimed to have set ambitious net-zero plans; but only 11 percent of them believe they have a robust and actionable sustainability strategy. And while 63 percent of the execs claimed to have achieved transparency on how sustainability decisions are made, fewer than a third say they are not confident their firm’s wider actions align with the ambitions being communicated to stakeholders.

This so-called ‘action gap’ is widely acknowledged. After years of skepticism, stalling and a lack of commitment, brands are finally taking sustainability seriously with hard-hitting goals and targets. But without the actions to back it up, most projects fail to gain traction internally, and therefore get stuck.

“The real blockers to sustainability are hidden inside companies and are often the result of what was considered sound management practice in the 20th century,” says Elisa Farri, VP of Capgemini Invent’s Management Lab, writing in the Harvard Business Review. She calls such management the “hidden enemies of sustainability: the prevailing organizational winds that tend to blow in the direction of routine and an incremental approach rather than sustaining a more radical and transformative journey.”

Does AI have the answers?

Two former Coca-Cola execs think they have developed the answer — a solution that will unlock common blockers and finally enable companies to take action that matches their ambition, whether that’s in reducing carbon or realising circular processes to eliminate waste. As with so many new solutions being created right now — including ensuring brand sustainability claims accurately reflect their achievements — the pair believe artificial intelligence (AI) holds the key.

In a nutshell, Ubuntoo is an online platform that uses AI to serve up suggested solutions and insights to a company’s sustainability challenges. Company execs can ask any question and prompt a search into a database of solutions and knowledge. The system retrieves the most relevant content, and then creates a summary with specific references to solutions and knowledge posts.

“Our AI platform combines the best human curation and AI to provide authoritative insight,” co-founder Peter Schelstraete tells Sustainable Brands®. The tech curates, categorizes, and analyzes knowledge and solutions drawn from both public and private data sources. It then indexes and organizes the data to find the most relevant information to answer questions.

Schelstraete is keen to point out that the B Corp-certified Ubuntoo is not simply a database of solutions; it is in providing “links and adjacencies” that it can create real value: “For example, solving an issue related to agave waste in Mexico can lead you to solutions in the areas of textile, building materials, animal feed, packaging or pharmaceuticals. Traditionally, people think of databases as a connection of individual entries. Ours is a connected web of solutions and knowledge.”

The ambition-action gap is real

The company already has an impressive roster of clients — including Amazon, Kimberly-Clark and PepsiCo. Previously, Schelstraete and fellow co-founder Venkatesh Kini held a number of high-profile roles at Coca-Cola — including CMO for Asia Pacific (Schelstraete) and Global VP Digital & Assets (Kini): “We’ve experienced firsthand the difficulty many businesses face in turning their ambition into action. This prompted us to quit our corporate careers and work to provide solutions to the planetary crisis we face,” he said.

Schelstraete draws a parallel between the current state of sustainability in companies and the digital landscape, say, two decades ago. Yes, there’s a significant amount of goodwill and ambition, but the execution “tends to be marginal and disjointed.”

“In most organizations, sustainability isn’t genuinely integrated into the growth strategy,” he said. “Too often, companies just engage in sustainability initiatives out of necessity rather than embracing it as a fundamental element through which their brands can create value. We’re driven by the vision of instilling a sense of possibility and action.

“Just as ChatGPT is beginning to supplant – or at least reduce – the routine tasks of copywriting and research, AI will soon support companies in getting the advice they need to turn environmental ambition into action.”

How does Ubuntoo work?

What sort of things are companies able to achieve using such a platform? Depending on the project, sustainability, supply chain, innovation and/or marketing teams can use the platform to find results. The objective of the AI platform is to exponentially accelerate the process of finding solutions and taking action. You might ask a simple question, such as: “I have two tons of discarded fishing nets. Who should I partner with to recycle and upcycle?” Or it might be a more technical question, such as: “How can I improve the effectiveness of bromelain extraction out of pineapple waste?”

Largely, the tech links clients to the most appropriate technology or partner to solve their problems. So, it might be a company like Cox Enterprises looking for ways to recycle coaxial cables, a company like The Clorox Company wanting to find ways to deal with hard-to-recycle waste or alternatives to plastic packaging, Or a company attempting to find alternatives to pesticides on plantations along their supply chain.

Based on a client briefing, Ubuntoo compiles an initial, AI-enabled “landscape” — mining a large amount of data (more than one billion datasets) including technologies, IP filings, companies and startups, academic articles and regular articles. It then selects the solutions and knowledge that are most relevant (“which is often less than 5 percent of what we find through AI”); and, through an iterative process with the client, it selects the most relevant solutions or partners to work with, to solve the issues.

“Sometimes, we match our client with one single solution provider,” Schelstraete says. “But often we connect them with an ecosystem of multiple partners. For waste projects, for example, we might need to find three partners – one to collect the waste, one to convert the waste, and one to upcycle the material into new materials or products.”

Can AI truly replace human expertise?

Can AI really be trusted to deliver the knowledge and insight that sustainability experts have spent years developing? Schelstraete is quick to make it clear that his technology, which has taken five years to create, will not replace human expertise. But what traditional consultants, and humans in general, have a hard time doing is scanning millions of pieces of content, summarizing those and creating links for ideation or solution discovery in a matter of seconds: “And it’s not just a matter of efficiency. AI tools allow us to expand our knowledge, decreasing the ‘unknowns’ exponentially.”

He highlights how Large Language Models – deep learning algorithms that can recognize, summarize, translate, predict and generate content using massive datasets – tend to be excellent in ideation and the discovery of adjacencies. In a recent study, researchers pitted university students against ChatGPT to see which produced better product ideas. ChatGPT won hands down, Schelstraete says. “Well-trained AI models can also discover unexpected adjacencies across disciplines — from physics to biology, and vice versa — which is very hard for any expert to do.”

So, what’s next for Ubuntoo? Like most AI developers, the focus is on making the technology even better to build credibility and trust. The two founders are committed to ensuring humans remain in the driving seat; but they also want to tackle other challenges associated with AI — which tends to prioritize search-engine-friendly, top-down perspectives and have a strong bias toward the English language.

“It makes it difficult for AI to incorporate practical knowledge from on-the-ground experience. Think about the knowledge on regenerative farming, passed over from generation to generation,” Schelstraete says. “The game-changing potential of these developments lies in the collective power of humans and artificial intelligence, working together in a common endeavour to put the natural environment first.”