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A good place to start when bringing artificial intelligence into your company is to see what distinguishes between effective and ineffective organizations when working on new technologies. The Boston Consulting Group went that path through a comprehensive survey of senior executives across 59 countries, ranging from 20 tanning sectors to more. While 4% are developing cutting-edge AI capabilities, 74% have found that they still feel they have not shown tangible value from their use of AI.
This report found six characteristics that distinguish these major companies.
- They don't just look at HR, IT and legitimate support features, they don't just uncover what they can do in their core business processes. “The general misconception is that the value of AI is primarily to streamline the operation of support functions and reduce costs.
- They are more ambitious: by 2027, we expect revenue growth expectations from AI to be 60% higher than other companies in more successful companies, and cost reductions by nearly 50%. This is due to positive actions on the core function. Three-quarters of the most advanced companies focus on corporate-level innovation cores, while only 10% of other companies use AI for productivity.
- They integrate AI in both cost and revenue generation. They are 4.5 times more likely to seek cost change and a third more likely to tackle revenue.
- They invest in fewer options and can be strategic with their approach. Large companies average around half of their AI-related opportunities. It's not that many.
- They focus on people and processes, not on technology or algorithms. Follow what the consultant calls the 70-20-10 principle. They put 10% of their resources into algorithms, 20% into technology and data, and 70% into people and processes.
- They moved quickly to the generation AI: Large companies used AI for predictive benefits, analysing historical and current data to estimate future events and trends, but delving into the opportunities for content creation, qualitative reasoning and orchestration of other systems,
Julian de Freitas and Elieek, marketing professors at Harvard Business School, compared them to successful, failed companies, in this case AI backfired and damaged brands, and enhanced their images while using new technology. They found that companies that use AI to over-focus on acquiring short-term economic value without considering how customer base sensibility and brand attitudes could be affected, often failing AI initiatives.
Levi Strauss complemented the human model by creating AI-generated models from various backgrounds, but critics viewed it as inexpensive shortcuts rather than actually hiring humans. LEGO angered fans on the company's website with images generated by AI that felt they were not responding to the company's brand identity, built on human creativity and craftsmanship.
Marketing professors provide these rules drawn from these mistakes and more successful corporate activities.
- Think long term: Ask if AI will really strengthen your brand over time or if it will save you time and money in the short term.
- Read the room: Understand how customers feel about AI now and how it affects how they perceive your brand's use. For example, Nike used AI and 3D printing to create custom sneakers for the 13 professional athletes he sponsored. “The bespoke sneakers reflect the unique journey of each Olympian and instantiation concept of using AI to support boundaries, personal excellence and innovation. Key themes related to the Nike brand.”
- Rather than being able to use Gadget Wizardry, it solves real problems. Identify ways in which AI can improve a particular customer experience along with your brand image.
- Put the human in the photo. Avoid making AI the main focus of your customer interactions. Professors can feel threatened rather than helpful.
One thing to note is that in recent research, four researchers from various universities have called the hidden penalty of using AI in the workplace. Two years after CHATGPT was launched, usage remains surprisingly low and could be more related to respect than the commonly cited lack of disability, knowledge and curiosity.
In this study, participants reviewed Python code written by another engineer, with or without AI support. The code itself was identical, but engineers rated the codewriter's ability on average 9% lower if they were thought to have been supported by AI. The ability penalty was more than twice as serious for female engineers, facing a 13% reduction in perceptual abilities compared to 6% of male engineers.
“The tech companies in our research were already doing more than most people. They formed dedicated AI teams, created incentives and provided training. However, these investments are lacking because they didn't address the threat of underlying capabilities,” the researcher wrote in the Harvard Business Review.
They recommend mapping your organization's penalty hotspots. Look for demographic vulnerabilities and power imbalances. Men who did not employ AI were the harshest critics of AI users in this study, so beware of many non-employment male reviewers and teams in senior roles.
Learn from other people's mistakes.
Cannonball
- Human Resources consultant John Bersin warns that AI cannot believe in handling complex and difficult decisions. Business decisions may seem logical and data-driven, but we interpret data differently, and our experiences and humanity define our responses. That experience and intuition comes from a combination of millions of years of history and billions of genes. They manifest in our minds and bodies as emotions, intuition, strengths, weaknesses, and ultimately as wisdom.
- Recurse Center (RC), an educational retreat for programmers in New York City, has developed a long and thoughtful position in AI. This is “whether you choose to accept or avoid AI in your work at RC, you need to build your own mental structure to grow as a programmer, people around you.”
- Trusting your team isn't so much of a relief, says entrepreneur Seth Godin. It's calming down for better.
Harvey Schachter is a Kingston-based author who specializes in management issues. He is the author of Sheila Whittaker, former CEO of both Canada and Kankon. When Harvey Does Not Meet Sheelagh: Leadership Email.
