Last week, I had the pleasure of attending the Digital Leaders Conference 2024, presented by the Swiss Association of MBAs (SAMBA). It was a fascinating event focused on how generative AI (GenAI) is reshaping the business landscape.
Here are some of my key takeaways.
Skate Where the Puck is Going, Not Where the Puck Is
A recurring theme was the need for companies to implement and test AI solutions now. While starting now may bring some immediate benefits, the primary reason to start now is to be prepared as an organization when AI becomes essential in the next 3-5 years.
Implementing AI: Key Considerations for Leaders
One analogy in a panel discussion compared teachers adapting their lessons for students embracing ubiquitous AI to a company’s struggle to determine how to implement AI safely and effectively while so many tools are readily available to employees. This analogy particularly struck me from my experience training teachers at eBackpack and watching their transition to a paperless classroom in a previous platform shift.
In determining a company’s AI strategy, leaders should consider two questions:
- How does AI impact my business model?
- How does AI impact my clients?
Technology should align with business needs rather than pursuing tech for tech’s sake.
One place to start may be finding ways to use AI to unlock existing troves of knowledge. An example we are all familiar with is stacks of reports that we need more time to read. If several groups are writing a status report, who takes the time to read and understand all of them? Meanwhile, how many would read an AI-generated summary of the trends and essential pieces of all the reports?
Additionally, leverage the current hype around GenAI to explore how other forms of AI and ML can benefit your company.
Upskilling and Recruiting: A Critical Priority
It was particularly insightful when the discussion turned to the fact that the most critical job openings are for cybersecurity, above AI expertise. The conclusion was that the bad guys also use AI tools to become more efficient.
However, upskilling the workforce is essential for AI adoption. While the amount and focus will vary with the role, all employees will need some level of AI training and that basic cybersecurity training should be a part of company onboarding.
However, a challenge is to reuse and access knowledge across domains without making every expert an AI expert—for example, using a police officer’s expertise to improve security without turning them into AI experts and developers.
One open question is: If AI reduces the need for entry-level roles, as expected, how will we ensure a pipeline of senior-level talent?
Process Innovation: A Key Differentiator
Understanding corporate processes is critical for AI success and overcoming the inertia of hidden processes. Streamlining and innovating these processes will differentiate successful AI implementations.
Conclusions
There was a broad consensus that all businesses are now digital businesses and that AI transformation has already begun. Staying current with AI developments is crucial. Experiment with new AI applications in your personal life; keep what works, delete what doesn’t, and consider how these functions can be utilized in a business setting.
Remember, while the recent hype around GenAI (sparked by ChatGPT) is significant, AI and ML have been evolving for years.
One of the panels was asked to close with simple, single-sentence words of encouragement to the audience related to AI, and I wanted to share them here.
- Be curious.
- Embrace it.
- Don’t panic.
- Make it part of your daily work routine.
I hope these insights spark some thought and discussion.