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A good place to start when bringing artificial intelligence into your company is to look at what distinguishes effective organizations from ineffective ones in grappling with the new technology. Boston Consulting Group took that path through a comprehensive survey of senior executives from more than 20 sectors and spanning 59 countries. It found 74 per cent feel they have yet to show tangible value from their use of AI while 4 per cent have developed cutting edge AI capability.
The report found six characteristics distinguishing those leading firms:
- They don’t just look at support functions such as HR, IT and legal but unearth what can be done in core business processes: “A common misconception is that AI’s value lies mainly in streamlining operations and reducing costs in support functions. In fact, its greatest value lies in core business processes, where leaders are generating 62 per cent of the value. Leveraging AI in both core business and support functions gives these companies competitive advantage,” the report states.
- They are more ambitious: The expectations for revenue growth from AI by 2027 in those more successful companies are 60 per cent higher than those of other companies and they expect to reduce costs by almost 50 per cent more. That stems from the aggressive action on core functions. Three-quarters of the most forward-looking companies focus on company-level innovation core to the business while only 10 per cent of the other companies do, instead leveraging AI, if at all, for productivity.
- They integrate AI in both cost and revenue generation: They are 4.5 times more likely to seek cost transformation and a third more likely to tackle revenue.
- They invest in fewer options, being more strategic in their approach: The leading companies pursue, on average, only about half as many opportunities as their less advanced peers in AI change. Less is more.
- They focus on people and processes rather than technology and algorithms: They follow what the consultants call the 70-20-10 Principle. They put 10 per cent of their resources into algorithms, 20 per cent into technology and data and 70 per cent into people and processes.
- They have moved faster into generative AI: The leading companies use AI for predictive advantages, analyzing historical and current data to estimate future events or trends, but also have been fast to delve into GenAI, opening opportunities in content creation, qualitative reasoning and orchestration of other systems.
Harvard Business School marketing professors Julian De Freitas and Elie Ofek also studied successful and unsuccessful companies, in this case ones where AI had backfired – damaging their brand – and compared them to those that have enhanced their image while using the new technologies. They found those businesses that were overly focused on using AI to capture short-term economic value without considering the sensitivities of their customer base and how brand attitudes might potentially be impacted often ended up with failed AI initiatives.
Levi Strauss created AI-generated models from diverse backgrounds to supplement human models but critics viewed it as a cheap shortcut rather than actually hiring humans. LEGO angered fans with AI-generated images on the company’s website that they felt didn’t live up to the company’s brand identity, built on human creativity and craftsmanship.
The marketing professors offer these rules drawn from those mistakes and the activities of more successful firms:
- Think long-term: Ask whether AI will truly strengthen your brand over time or just save you time and money in the short run.
- Read the room: Understand how customers currently feel about AI and how that might affect how they perceive your brand’s use of it. Nike, for instance, used AI and 3D printing to create custom sneakers for 13 professional athletes it sponsored. “The bespoke sneakers reflect the unique journey of each Olympian and instantiate notions of using AI to help push boundaries, personal excellence and innovation — key themes associated with the Nike brand,” notes Prof. Ofek.
- Solve real problems rather than just seeing how fancy you can be using the gadget wizardry: Identify how AI will make specific customer experiences better in line with your brand image.
- Keep humans in the picture. Avoid making AI the main focus of customer interactions, which the professors warn can feel threatening rather than helpful.
Something else to watch out for is what four researchers from various universities in a recent study call the hidden penalty of using AI at work. Two years after ChatGPT was launched, usage is still surprisingly low and it may have to do with esteem more than the commonly cited obstacles, knowledge or lack of curiosity.
In the study, participants reviewed Python code written purportedly by another engineer, either with or without AI assistance. The code itself was identical but the engineers evaluated the competence of the code writer 9 per cent lower on average if they were thought to have been assisted by AI. The competence penalty was more than twice as severe for female engineers, who faced a 13 per cent reduction in perceived ability compared to 6 per cent for male engineers.
“The tech company in our study had already done more than most. They formed dedicated AI teams, created incentives and provided training. Yet, these investments fell short because they didn’t address the underlying competence threat,” the researchers write in Harvard Business Review.
They urge you to map your organization’s penalty hotspots. Look for demographic vulnerability and power imbalances. Males who had not adopted AI were the harshest critics of AI users in the study so be alert to teams with many non-adopting male reviewers in senior roles.
Learn from the mistakes of others.
Cannonballs
- Human resources consultant John Bersin warns we can not trust AI to handle complex, difficult decisions. While a business decision may seem logical and data-driven, we each interpret data differently and our experience and human nature define our reaction. That experience and intuition come from millions of years of history and billions of gene combinations; they manifest in our minds and bodies as emotions, intuitions, strengths, weaknesses – and ultimately as wisdom.
- The Recurse Center (RC), an educational retreat for programmers in New York City, developed a long, thoughtful position on AI, which concludes tersely: “Whether you choose to embrace or avoid AI in your work at RC, you will need to build your own mental structures to grow as a programmer. When using AI, use it to amplify your ambitions, not to abdicate your agency. And regardless of what you do, be curious about and kind to the people around you.”
- Trusting your team isn’t settling for less, says entrepreneur Seth Godin. It’s settling for better.
Harvey Schachter is a Kingston-based writer specializing in management issues. He, along with Sheelagh Whittaker, former CEO of both EDS Canada and Cancom, are the authors of When Harvey Didn’t Meet Sheelagh: Emails on Leadership.