Behind the Numbers: Using AI at Work - Part 2
Podcast Information:
- Title: Behind the Numbers: an EMARKETER Podcast
- Episode: Using AI at Work: Part 2—How companies are using AI and tips for employees on how best to use it
- Release Date: April 4, 2025
- Host: Marcus
- Guests: Arsene Alice (AI and Technology Analyst), Gajo Sevilla, Henry Powdery (SVP of Media Content and Strategy)
- Description: This episode delves into the practical applications of AI in the workplace, exploring how companies are leveraging AI technologies and providing actionable tips for employees to effectively integrate AI into their daily tasks.
1. Introduction and Icebreaker
The episode kicks off with Marcus welcoming listeners and introducing the returning guests, Arsene Alice and Henry Powdery. To set a light-hearted tone, the hosts engage in an amusing discussion about extreme running feats:
- Henry Powdery shares, “It took him 20 months. That's a long time, Kevin. The greatest.” (01:11)
- The conversation humorously touches upon human endurance limits, emphasizing the challenges of long-term commitments, paralleling it subtly to the complexities of AI adoption in businesses.
2. The AI Backlash: Understanding Employee Resistance
The core discussion begins with Marcus referencing an insightful article by Grace Harmon, highlighting significant resistance among employees towards Generative AI (Gen AI) adoption.
- Key Statistics:
- 41% of C Suite executives believe Gen AI is causing internal strife.
- 31% of employees admit to sabotaging their company's AI strategies.
- Higher sabotage rates are noted among Gen Z and millennials, with 1 in 10 workers tampering with performance metrics to undermine AI's effectiveness. (03:12)
Reasons for Resistance:
- Diminished Value and Creativity: 33%
- Fear of Job Replacement: 28%
- Increased Workload: 24% (03:12)
Gajo Sevilla probes, “Are we heading towards an employee AI backlash?” leading to a nuanced discussion:
- Gajo: “I mean, I wouldn’t say it’s wide scale, but possibly in certain situations, certain industries... if employees are left to their own devices.” (04:03)
- Henry Powdery: Emphasizes the leadership’s role in mitigating backlash by clearly communicating AI’s role as an augmentative tool rather than a replacement. “If companies could tell that story more clearly... empowering them with resources...” (07:04)
3. The Perception Gap: Executives vs. Employees
A significant chasm exists between how executives and employees perceive AI adoption within their companies.
- Survey Insights:
- 70% of executives believe their AI strategies are strategic and successful.
- Only 40% of employees share this sentiment, a 30 percentage point gap. (05:03)
Henry Powdery attributes this disconnect to inadequate communication and resource allocation: “...leader ship not giving any resources out to their teams to figure this stuff out.” (07:04)
4. Identifying Business Value: Overcoming the Productivity J Curve
Discussing the challenge of translating AI technology into tangible business value, the hosts reference Professor Eric Brynjolfsson’s concept of the "productivity J curve" where initial productivity may dip before rising.
- Gajo Sevilla: Advocates for aligning AI solutions with specific business outcomes such as cost reduction through automation or revenue growth via AI-driven personalization. “You’re trying to solve problems... AI is just a convenient and measurable tool...” (10:45)
- Henry Powdery: Suggests evaluating AI’s impact from a financial perspective, focusing on both revenue acceleration and cost reduction. “What can generative AI help you accelerate... reduce expenses...” (12:03)
5. AI Accuracy and Reliability Concerns
A critical examination of AI’s reliability, particularly in information accuracy, is presented through a study by Columbia Journalism Review and the Tao Center for Digital Journalism.
- Study Findings:
- AI models incorrectly cited sources in over 60% of queries when tested with real news excerpts. (14:19)
Henry Powdery: Acknowledges the complexity of the news ecosystem and the inherent challenges for AI in accurately attributing sources. “The language models already have a challenge... the language model doesn't say I don't know...” (15:34)
Gajo Sevilla: Highlights the programming limitations of AI models, noting their tendency to generate responses even when uncertain. “They’re just programmed to have answers and solutions.” (15:38)
6. Practical Tips for Using AI at Work
The episode concludes with actionable advice for employees on effectively utilizing AI tools in their professional lives.
From Alex Fitzpatrick of Axio:
- Be Specific: The more precise your requests to AI, the better the outcomes.
- Follow Up: If the initial AI response is unsatisfactory, refine your request with clear instructions for improvement. (17:39)
From Henry Powdery:
- Use Audio Interfaces: Recording ideas verbally to overcome writer’s block and streamline the proposal-writing process. “...record myself... transcribe the whole thing and just talk for 30 minutes...” (17:39)
- Leverage AI Training Features: Utilizing tools like Claude Styles to train AI on personal writing styles, ensuring outputs align with individual voices. “By training it on some of the pieces that I'd written... it does a lot better job now.” (18:55)
From Gajo Sevilla:
- Start Small with AI Pilots: Implement AI on a single team or department to measure effectiveness before wider adoption. “Pilot projects give us good feedback and most of the kinks are worked out...” (19:56)
- Measure Success Effectively: Establish clear metrics such as time saved or error reduction to evaluate AI’s impact. “You could use time saved... error reduction...” (20:10)
Additional Tips from Marcus:
- Check AI’s Work: Always fact-check AI-generated content to ensure accuracy, especially given the high incidence of AI hallucinations.
- Be Polite: Incorporating courteous language can enhance AI chatbot interactions. “Researchers have found that using words like please and thank you improves AI chatbot performance.” (21:10)
7. Conclusion
Marcus wraps up the episode by thanking the guests and the production team, emphasizing the importance of ongoing dialogue about AI in the workplace. The hosts encourage listeners to apply the discussed strategies to navigate the evolving AI landscape effectively.
Notable Quotes with Timestamps:
- Marcus: "If someone close to me said, 'Marcus, I'm thinking about running for three days straight,' I'd be like, don't." (02:15)
- Henry Powdery: "A lot of this is driven by a need to get more efficient, more nimble, more creative." (07:04)
- Gajo Sevilla: "The narrative should be that it's a tool that can help augment but not replace your employees." (07:33)
- Henry Powdery: "The bottom line is the bottom line where we're using these tools in order to run more efficient and more profitable businesses." (12:03)
- Marcus: "Check its work. Make sure you fact check all that stuff." (21:10)
- Henry Powdery: "Using audio as the interface... just let you kind of go." (17:39)
Key Takeaways:
- Employee Resistance to AI: Miscommunication and lack of resources contribute to employee sabotage and resistance towards AI adoption.
- Leadership’s Role: Clear communication and positioning AI as an augmentative tool are crucial in minimizing backlash.
- Bridging the Perception Gap: Aligning executive optimism with employee experiences through strategic implementation and support.
- Ensuring AI Accuracy: Vigilance in fact-checking AI outputs is essential, especially in information-sensitive areas like news.
- Practical AI Usage Tips: Specificity, follow-ups, audio interfaces, pilot projects, and personalized training can enhance AI’s effectiveness in the workplace.
By addressing these areas, companies can better integrate AI into their operations, fostering a collaborative environment where technology empowers rather than replaces employees.
