Welcome to season 1, episode 7 of Breaking with Tradition, Catalyst’s podcast that explores trends and ideas that will impact the future of the global workplace. This episode is called AI and the Future of Pink-Collar Jobs.

As AI technology rapidly evolves, a troubling new gender gap has emerged, especially among younger workers: 71% of men ages 18-24 say they use generative AI weekly, compared with 59% of women. This gap threatens to widen existing disparities, especially frontline women in “pink-collar” sectors such as customer service, healthcare, and education.

Join host Victoria Kuketz as she chats with Ana Kreacic, Partner and Chief Knowledge Officer of Oliver Wyman Group and COO of the Oliver Wyman Forum, and Terry Stone, Managing Partner Global Health and Life Sciences and Former Managing Director, Americas, Oliver Wyman to discuss the urgent and important need for inclusive upskilling initiatives, incorporating AI into companies’ future vision, and tapping the leadership of Gen Z.

Tune in as we unpack how generative AI could both displace and empower, and what steps companies can take to create a more equitable future of work for all.

Host and guest

Victoria Kuketz, Director, Corporate Engagement, Canada, Catalyst

LinkedIn | Bio

Ana Kreacic is a Partner and Chief Knowledge Officer of Oliver Wyman and COO of the Oliver Wyman Forum – the think tank and platform for engaging business, public policy, and societal leaders to act on shared challenges. With over 20 years of consulting and operating experience, Ana is known for her ability to blend customer insight with business strategy and leadership effectiveness. A frequent speaker and author, Ana’s work has been featured in the World Economic Forum, Wall Street Journal, and MIT Sloan, to name a few. Ana is passionate about empowering women and youth.

LinkedIn | Website

Terry Stone is Vice Chair and Interim Global Lead taking on two strategic priorities for Oliver Wyman. One is as interim Global Leader for Health and Life Sciences focused on accelerating the growth of our Life Sciences businesses in the US and Europe. A second critical firm priority which Terry leads is a project for our CEO to accelerate the transformation of OW’s own business and operating model in response to Artificial Intelligence. Our priority is to identify how consulting overall, and our OW’s business is likely to be impacted by the opportunity and threats that AI creates for strategic advisory businesses.

LinkedIn | Website

In this episode

• 1:41 | Tell us about yourselves! Ana and Terry fill us in on what excites them as AI practitioners.
• 4:29 | The AI gender gap. Our guests break down the emerging AI usage gap between men and woman.
• 8:22 | “Pink-collar” sectors and AI. Terry defines what a “pink-collar” job is and how they’re perceiving new AI technology.
• 14:49 | Performing at the top of your license. How can we convince reticent AI users of its huge potential for positive change?
• 20:11 | AI tips & tricks. Terry reflects on her experience and what works on implementing AI policies at work. Ana brings in the “pink-collar” specificity.

Favorite moments

• 2:17 | Ana: For me, [the exciting part about AI] is the opportunity for positive change… It’s a time that requires a lot of reflection if we’re going to get it right.
• 3:21 | Terry: AI is going to be the single biggest, disruptive force or catalyst for change in business in my entire career.
• 11:50 | Terry: When [AI use is] done well, you can easily see 15-20% productivity improvements in key areas.
• 12:19 | Terry: There’s still a lot of fixation on AI as “driving efficiency.” I think the best companies are thinking about “How does AI serve as a catalyst for me to reimagine everything we do?”
• 15:25 | Ana: When ChatGPT was launched, all of the assessments said it was a very smart eight-year-old… Now we’re getting in the realm of it being an average, maybe C-level PhD student.
• 16:22 | Ana: If you look by gender, women on average will say that they are less aware, in the same company, of AI initiatives. They are less aware of changes their company has made. They are less likely to participate in trainings.
• 18:44 | Terry: The truth of the matter is, AI is going to impact your job. So, you getting smarter about AI will enable you to use it to do your job better… The more you lean in, the more you’ll get out of it.
• 22:02 | Terry: [When it comes to AI implementation], you have to think about both breakthrough business impact and things that are broad-based and easy but that make everyday users’ lives’ easier.
• 25:46 | Ana: How is it that 40% of Gen Z prefer an AI manager? Part of the reason is because they have no fear of asking any question to AI. And the way they ask the question, they know they’re not going to be judged for how they’re asking the question or what they’re asking about. Also, it’s available any time.

Mentioned on the Pod

• World Economic Forum: How to stop women falling behind on generative AI in the workplace
• Oliver Wyman Forum: How generative AI is transforming business and society
• Forbes: 46% of Gen Z leans more on AI than their managers, says new study

Research you can use

• Blog: Global CEOs share insights on AI implementation
• Blog: What is ‘responsible AI’? Panelists weigh in
• Blog: Leverage AI while avoiding its risks and biases
• Webinar recording: How to use generative AI free of gender and racial bias (Supporter Only)
• Explainer: Responsible artificial intelligence for inclusive workplaces (Supporter Only)
• Tool: Use AI to attract a more diverse candidate pool (Supporter Only)

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The post Episode 107: AI and the Future of Pink-Collar Jobs appeared first on Catalyst.

Whatever the general public may think of AI, businesses are on board, seeing the great potential of AI for optimizing existing systems and creating new ones. AI is no longer viewed as simply an option for most industries, but as an inevitability.

As businesses with the agility and budgets lead the charge on the development and implementation of AI, and others begin to follow, it can be easy to move at the speed of innovation without viewing AI through a human lens. In this spirit, panelists convened at the 2024 Catalyst Honours in Toronto on 7 October 2024 to discuss “Shaping an Inclusive Future Through Generative AI.”

Kathleen Taylor, Chair, Element Fleet Management, Altas Partners, and The Hospital for Sick Children, spoke about the portfolio of organizations she works with, saying they are generally optimistic about an AI-enhanced future of work. “There’s such enormous opportunity associated with all of this,” she said.

This sentiment was echoed by discussion moderator David Morgenstern, President, Accenture Canada, who said, “We published a paper at Microsoft this spring that said even traditional Canadian adoption [of AI] would add the equivalent of an insurance or retail sector to Canada.” That translates to an annual economic windfall of $180 billion in labor productivity gains by 2030.

AI can assist in innovation for good

Panelists then shifted their focus to implementation. Jennifer Freeman, CEO of PeaceGeeks,  highlighted AI’s impact on bridging the gaps between users and government. “We’re really utilizing AI in our digital tools as an equalizer,” she said.

For immigrants, there are many barriers (like language and technology) to accessing resources. PeaceGeeks partnered with Accenture to create an AI virtual career coaching platform that can help people practice interviewing, soft skills, and job matching for permanent residency.

As of 7 October 2024, the platform, which rolled out in June, has already had over 100,000 unique users.

AI can perpetuate current biases

Panelists agreed that a healthy dose of caution is needed when creating platforms that rely on AI. Pamela Pelletier, Country Leader & Managing Director, Canada, Dell Technologies, said, “It’s all about the data. Garbage in, garbage out. If you have data that is skewed or that is biased, then you’re going to have a problem.”

She gave the example of AI chatbots, which can “hallucinate”. “Where does ChatGPT get their information from? Twitter, whatever, all these places. So, the data itself is potentially biased.”

Aneela Zaib, Founder & CEO, emergiTEL, said, “The fact is that the LLM (large language model) models that we have on our hands currently, we don’t know how they’re trained or which data they are trained on.”

AI must be fed the right data

What can be done to combat this issue? How can we prevent the same blind spots in the future?

Zaib is already working on solutions. “One of the ways we have tried to overcome [this] is we have fine-tuned these models based on the dataset that are inclusive in nature already. So, when you give a dataset to this tool which is already inclusive and you define set prompts (and there’s a lot of detail…that we can go crazy over), the bottom line is that you have to be very careful in using these systems, giving them the guardrails, and at the same time auditing these systems at the end with the results that you are getting.”

Her company’s tools deliver diverse job candidates to client companies, and AI is part of those tools. When they audit the results that AI delivers, if they find a job or a skillset that isn’t being filled by candidates in certain communities, they analyze those results, fine-tune them, and run the AI model again. Ongoing stewardship of these AI tools and models is part of the process, especially when the work is so important. Zaib said, “Diversity is a practice that we have to do every day.”

DEI and AI can work together

Pelletier echoed this sentiment, saying, “We have the opportunity with the tech that exists now to actually bring people in who have been historically forgotten or left behind.”

Organizations that use AI must do their part. Pelletier said, “As an organization, we have the responsibility when we’re training models to have that data reflect the values we have as an organization. So, it is really important that we take that data and we curate the data to reflect those values… and then we’ll have a very positive outcome.”

She added that DEI and AI can and should work together to further humanity’s best interests. “We need to have our DE&I representation, those folks, at the table at the beginning as we implement the AI projects. And they need to have the ability or authority to hit that pause button or that stop button. If one were analyzing the data, if something is inappropriate, they can pause that and go and correct it,” she said.

Be intentional with AI

As organizations rush to add AI to various aspects of their businesses, it’s important to take the time to do it correctly. If a company doesn’t have high customer service traffic, it probably doesn’t need an AI chatbot. If a company has a large marketing department, it probably doesn’t need to train AI to write articles. And if a company cares deeply about its values, it shouldn’t license an LLM trained on biased datasets.

Taylor summed it up perfectly: “We can make this work, as long as we’re building capably, testing well, utilizing but then coming back around and making sure that what comes out the other end is exactly the outcome we would have hoped for, whether that’s a new recruit, a system that’s delivering a new customer offering, whatever it may be.”

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The post Global CEOs share insights on AI implementation appeared first on Catalyst.