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Navigating the Future of Work with AI: Insights from Industry Leaders

4 MINUTE READ | March 26, 2024

Navigating the Future of Work with AI: Insights from Industry Leaders

Navigating the Future of Work with AI: Insights from Industry Leaders

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Natalie Sherman, Product Marketing Lead

As PMG's Product Marketing Lead, Natalie Sherman bridges the gap between product development and the broader market, partnering closely with PMG's technology team to oversee marketing communications and product positioning for PMG's technology platform, Alli. With previous stints at Ring and Moen, she brings a wealth of industry insights, marketing expertise, and innovative thinking to every conversation.

In an era where generative AI continues to transform how we approach work and creativity, PMG stands at the front of the line, offering cutting-edge marketing solutions through our AI-powered platform, Alli. At this crucial moment, with technology evolving quickly, PMG brought together industry leaders and AI experts to discuss how individuals at the intersection of AI and work are adapting to the latest advancements.

At the aiVolution: Connecting Innovation and Strategy event in Austin, Texas, earlier this month, PMG’s panel on the practical applications of AI and its future in the workplace included Google Field CTO Dustin Williams, Shipyard Co-Founder and CEO Blake Burch, Kargo VP of Marketplace Strategy Kyle Green, and PMG Technical Solutions Senior Manager Brianna Gaskill. Each voice, tapping into their deep leadership and ‌technical knowledge, offered unique insights and ‌perspective into how AI can transform work for the better. 

A recurring theme at the event was how we must shift our mindsets to one of future “big idea” thinking as the scale and power of AI compels us to tackle larger, more complex tasks compared to some of the monotonous elements of day-to-day work. Google’s Williams posited that AI will quickly take over these tedious tasks, freeing individuals to engage in work that genuinely interests them. He emphasized the importance of focusing on future challenges rather than being bogged down by past problems. 

“Stop solving yesterday’s problems. They are little problems, solve the big problems of tomorrow instead.” – Dustin Williams, Google

Kargo's Green advocated for the value of using AI as a tool for rapid learning and skills development. He recommended that everyone start using AI to learn about new topics and develop and refine their professional and personal skills. 

“Hey chatbot, what’s street epistemology? Explain it to me like I’m 10 years old.”

He emphasized the importance of community engagement and experimentation for gaining deeper insights into AI’s full capabilities. According to Green, activities like going to meetups and events and talking to people (not chatbots) are crucial next steps for learning more about how to apply AI in work, as people in different disciplines or industries can provide advice, guidance, and additional tips and tricks you wouldn’t have thought of otherwise.

From a technical perspective, PMG’s Gaskill noted that it’s important to use discernment when engaging with these technologies as different models provide different guidance, making learning and knowledge-seeking from AI confusing. For example, she said, you can use a RAG (retrieval-augmented generation) or LLM (large language model) and receive different perspectives on whatever subject you’re querying about. With so many AI models to choose from, Gaskill recommends people start with the basics, then add complexities to your queries while keeping in mind that there’s almost always another engineer who has—or is trying to—solve the same problem you’re facing, so engaging with your community and network allows for you to learn from them just as easily as an AI chatbot. 

Gaskill also criticized the hasty adoption of AI without a clear strategy, stating that simply deciding to use AI isn't enough. It’s important to match your vision with practical skill-building to deliver successful implementation. 

“‘We are going to use AI,’ period, is not a strategy for implementing AI. We must combine our vision with tactical and practical skill-building for successful AI adoption." – Brianna Gaskill, PMG

Adoption looks different for everyone. Gaskill noted that at PMG, the team’s frontline software engineers regularly have generative AI tools open as an integral part of their workflow, as they use it for‌ every task, including coding. She raised the question of how we might achieve such a comfort level with generative AI across all levels and backgrounds in the workforce, enabling its accessibility and equity for everyone. Thus, there’s a critical need for continued support with coaching, the normalization of these technologies, and consistent skill development when introducing new technology and tools like generative AI capabilities to ensure an effective rollout and implementation. 

Shipyard Co-Founder and CEO Blake Burch suggested that to ease people into using AI, it’s beneficial to begin with applications that tackle mundane tasks. This, he argued, builds comfort and familiarity with AI technologies. Ideas for getting started could be creating daily to-do lists and prioritizing tasks or running weekly reporting. Figure out what tiny tasks your team is currently taking the time to do regularly and start there. He recommended that leaders avoid starting with large engineering epics or complete tech overhauls—in principle, that sounds easy but can be a huge challenge in practice. 

Similarly, Gaskill discussed how AI can help with creative ideation. Creative teams can pair their most eccentric ideas with AI to visualize, test, and iterate quickly.

How can you get started leveraging AI? Our panelists gave their take:

Discover New Insights: Green suggested using AI to simulate conversations between personas to gain insights about your products or strategy. He said, “[For example,] reenact two people having a conversation. One is a marketer, and the other is a software engineer. They are discussing a new product for turning product data sheets into slides. What would their conversation be about?” 

Ensure Clarity in Your Queries: Burch reminded us that AI requires clear instructions to be effective. As users get more comfortable interacting with a model, their inputs start to shrink as they give less prompting. Remember: The more information you give a model, including a description of your tone, brand, or other stylistic elements, the better responses you’re going to get in return.

Experiment Regularly: Gaskill encouraged leaders to take a hands-on approach, urging teams to explore and experiment with AI tools. She said, “We must be good leaders and set the example for our teams, and perhaps most importantly, it's not a good idea to put company data into open models.”

Activate Prompt Engineering Best Practices: Lastly, Williams highlighted the significance of prompt engineering as an essential skill for fine-tuning AI interactions via crafting effective prompts that guide AI responses accurately. He emphasized that markdown is a formatting tool normally used to structure text with headers and lists for clarity, but can also be applied with AI to help beginners design prompts and receive improved outputs. Research and practice different prompt engineering concepts to improve your skills.

Teams should continue putting revolutionary tech into their platforms and getting new AI-powered products to market. Different niches can be served by different models, and there's so much opportunity in the market to launch better AI-powered products—AI development isn't all fad-based. In referencing her team’s recent work, Gaskill outlined how they are leading the development of several new features within Alli with the goal of further integrating AI technologies. These initiatives seek to offer even more AI-powered features to PMG clients, enhancing the effectiveness and efficiency of marketing strategies through data-driven insights.

The event offered valuable perspectives on using AI to improve our work lives, emphasizing the need for a balanced approach that considers people, privacy, and practicality. As we continue to explore AI’s endless potential, it's clear that thoughtful engagement and continuous learning will be key to unlocking its full benefits.

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