It’s hard to believe that artificial intelligence (AI) has been around for seven decades. Recently, the topic has exploded with the evolution of generative AI. Now, we’re hearing more about the world of AI and what it means for the future of work on a daily basis.
But when it comes to understanding how AI works, knowing when to use it, and how to integrate AI into our existing workflows for better efficiency, it can be challenging. So, to dive into all things AI, we invited Dr. Lisa Palmer, Chief Strategist at Dr. Lisa AI for a thought-provoking conversation with Seismic’s CMO, Paige O’Neill.
They explored the rise of AI, stories from the field, and how go-to-market (GTM) teams can experiment with and leverage AI. They also polled webinar attendees, which included leaders in technology, healthcare, financial services, and more, to learn about their organizations’ current status and future plans for AI.
Let’s dive into some of the biggest takeaways!
Understanding the different types of AI
While everyone is using the term AI broadly, Dr. Lisa emphasized the importance of understanding the different types of AI that currently exist.
- General: Also known as strong AI, this is the hypothetical ability of an intelligent agent to understand or learn any intellectual task that a human can.
- Narrow: Weaker AI systems that operate within predefined boundaries and rely on algorithms, rules, or data to accomplish a task. This is what we have today.
- Generative: A subnet of AI that focuses on creating and generating new data. This includes things like predictive texting or types and is what we keep hearing about in the media today.
Between the various types of AI and the fact that more than 3,500 tools have been released so far this year, it’s impossible to keep up. Thankfully Dr. Lisa provided actionable ideas and best practices for attendees.
Picking up productivity diamonds
Nearly every industry is being impacted by AI, and it’s created an inflection point for organizations. Those who are making an effort to embrace it already have a leg up on their competition and will only continue to extend their lead. To get a better understanding of where our attendees stand with AI, we took to the polls.
If you’re still looking for ways that your organization can use AI, Dr. Lisa suggested looking for those ‘productivity diamonds.’ These are tasks that can be done in partnership with AI. What are the tasks that your team is getting bogged down by? Or, are there areas that you’re having difficulty scaling? These are natural opportunities for AI that can drive revenue and elevate productivity.
One area that’s ripe for AI success is content personalization across revenue roles. With AI, organizations can truly personalize every outreach and interaction they have with prospects and customers. This can lead to faster sales cycles, improved productivity, and higher customer satisfaction. Other areas include information accessibility and guided selling. And while organizations may want to go as far and as fast as they can, Dr. Lisa reminded everyone that there will be situations that fail. However, she challenged attendees to shift their perspectives to accept and learn from these failures.
Getting started with AI
If you’re ready to embrace the new era of AI, Dr. Lisa suggests:
- Investing in education: It’s important to take the time to upskill yourself, your leadership team, and your entire workforce on data and AI. Look for ways to provide training and education into your workflow so that everyone understands best practices, safety, and company regulations around using AI.
- Adjusting culture: In order for AI to work effectively, your company’s culture needs to be highly collaborative. The organizations that operate in silos will struggle in the era of AI. Look for ways to break down those silos and approach AI in an agile and adaptive way.
- Budgeting wisely: Organizations tend to budget a lot of money for technology and, but fail to budget adequately to ensure we actually create value from these tools. Be sure to budget equal amounts for the technology itself and for adoption.
- Reassessing job roles: Reassessing jobs every one to three years doesn’t work anymore. Dr. Lisa recommends reassessing job roles every 90 days in order to identify ways that AI can free up time for more high-value work.
We’ve entered the era of disruptive innovation. While AI isn’t poised to replace blue-collar jobs, it’s a huge leap forward in optimizing cognitive work and manual tasks. By replacing these tasks with AI, revenue teams will have more time to focus on high-impact, critical, and strategic work that will lead to greater efficiency and productivity. The combination of AI and humans has created a powerful augmented working environment that many industries and organizations will benefit from.
Ready to learn more?
These tips and best practices only scratch the surface of what Dr. Lisa shared. So if you want to hear more of the conversation for yourself, you’re in luck. You can access the entire webinar on-demand. Or, check out some frequently asked questions about AI below!
AI FAQs
What are the key differences between general, narrow, and generative AI?
The key differences lie in the scope of capabilities. General AI can perform any human intellectual task, narrow AI operates within predefined boundaries, and generative AI focuses on creating new data, such as predictive texting.
How can organizations identify and prioritize tasks suitable for AI integration, especially in the context of “productivity diamonds?”
Organizations should pinpoint areas of operational difficulty or scalability issues. Leveraging AI in these areas can increase revenue, elevate productivity, and speed up sales cycles. Looking for some ideas on how to get started? Check out our ebook, The State of AI in Enablement, to learn how organizations use AI.
How can companies effectively address the challenges of cultural change and collaboration when adopting AI?
Organizations should foster a highly collaborative environment, breaking down silos and approaching AI with agility. Additionally, investing in education, budgeting wisely for technology and adoption, and reassessing job roles every 90 days can contribute to a successful transition to an AI-centric working environment.
