David Wilkins, chief product, marketing and strategy officer at DanceNeuron, is a proven senior executive with over 20 years of SaaS experience in the field of human capital management. He has a variety of leadership experience in strategy, product development, marketing, sales support and sales.
TalentNeuron provides workforce intelligence to help organizations optimize talent strategies, source key skills and future workforces. Using data from over 28,000 sources, it provides insights on labor market trends, talent supply and demand, and location strategies to serve Fortune 100 companies and global businesses.
How can AI revolutionize labor planning and talent analysis in today’s competitive labor market?
Recent years mark a critical shift in workforce intelligence. For TalentNeuron, the world has turned to our favor. After two decades of collecting and sorting large amounts of labor market data, AI has unlocked the ability to extract unprecedented insights at scale.
What makes this transition really powerful is the ability of AI to identify unexpected talent pools and skills distributions in previously neglected GEOs. Consider how American companies discovered a rich talent pool in the former Soviet state after the collapse of the Soviet Union. Early porters gained a huge competitive advantage in emerging technology centers in Russia, Ukraine and the Baltic by identifying and obtaining highly skilled IT and engineering talents. Today, AI helps organizations discover similar opportunities systematically and at scale, revealing hidden talents that might otherwise not attract attention. This pattern recognition capability allows companies to detect inequality in the global labor market that can be transformed into strategic advantages.
I have witnessed first-hand how this affects the strategic workforce program. Now organizations can make smarter decisions about talent acquisition and management and execute this data at an amazing speed.
What is AI’s role as a strategic consultant for companies facing talent shortages and skills gaps?
The power of the AI model lies in its ability to conduct a comprehensive analysis of talent supply, demand and emerging skill trends – providing organizations with a data-based strategic decision-making basis. This intelligence enables businesses to develop evidence-based talent strategies, with internal stakeholders and external consultants using AI-derived insights to address skill gaps through targeted, high-skilled, reattacks or strategic recruitment programs.
However, it is crucial to understand that AI is the enabler, not the alternative strategic guidance. At TalentNeuron, our partnership with Fortune 2000 requires the blend of data intelligence and human expertise. Although AI excels in pattern recognition and data analysis, a nuanced understanding of the organizational environment, culture and long-term business goals comes from our experienced team. Our approach combines AI’s analytical capabilities with human strategic insights to ensure our customers receive data-driven intelligence and thoughtful, contextual guidance to address their unique challenges.
This synergy between AI capabilities and human expertise can provide more valuable results than any one can achieve.
How can companies effectively leverage AI to align their talent strategies with long-term business goals?
AI provides the ability to observe and internalize talent insights at scale, enabling HR and TA teams to build strategies that align with future business goals. We can liken this process to a car heading to the destination and what information the driver needs to get there. In the past, organizations focused on mechanical information in “cars” – the talent insights they gained from within the business. AI-driven talent analysis enables companies to consider “roadmap” and “destination” in this analogy, where market conditions and business objectives can be incorporated into the strategy because information is easily accessible.
Can you explain how TalentNeuron’s AI model predicts labor demand and determines emerging skills?
AI technology forms the basis of how we understand the landscape of skills and labor needs. Essentially, our system processes millions of global job postings every day, cleaning and analyzing this vast dataset to reveal detailed patterns of skill requirements across roles, locations, and organization types.
What makes this really powerful is our skill evolution model. It not only shows you the skills you need today, but also maps the skills to the evolutionary curve, clearly identifying which are emerging, which are becoming core requirements, and which are becoming obsolete. For our Fortune 2000 clients, this provides an unparalleled view of where a particular role is going and what features they need to build in the workforce.
We also make this intelligence easier to access through our AI assistant Sannappy. Unlike typical AI chatbots, Synappy draws only from our data, so each insight is based on real-world evidence. This means our customers can quickly extract meaningful insights about talent trends without having to get involved with raw data.
What are your trends in how organizations can use AI to lead the skills shortage and prepare for future talent needs?
Organizations are increasingly using AI to perform scenario modeling and predict their future employee needs. With the visibility of global talent, organizations can identify previously unused skills. They are working with platforms such as TalentNeuron to proactively determine how their talent needs will evolve based on advances in AI, automation and broad digital transformation. For example, the rise of proxy AI, which has a model that makes independent decisions in the workflow, making some human skills obsolete. As artificial intelligence continues to increase the various tasks that can be accomplished, organizations should plan for this workplace revolution.
How does AI help businesses anticipate and adapt to evolving global labor market trends?
AI provides real-time labor market intelligence to businesses, which will enable them to predict changes in talent availability, wage trends, and skills demand. AI-powered talent analytics platform integrates past and present data to provide a 360-degree labor market. The organization can then make decisions in the right place to extend what kind of hybrid work model is most attractive to the target professional group.
How can organizations integrate AI-driven insights into their existing systems for more effective hiring and workforce planning?
Working with platforms like TalentNeuron, organizations can enhance their current talent approach by understanding the skills they have, the skills they need to achieve their business goals, and how and what skills they will be required to achieve that goal. Part of this process may involve API integration that connects labor market data directly to the human resources system and decision-making platform. For less involved insights, tools like Synappy allow organizations to ask specific labor market questions and incorporate simple answers directly into their strategy.
Can you share examples of how TalentNeuron data can help organizations make influential decisions about workforce locations and diversity strategies?
An example is our recent work at the Baton Rouge Health District. The eight network of healthcare organizations in Baton Rouge, Los Angeles, is striving to span employees across numerous positions, compete for population declines, more attractive healthcare jobs elsewhere, and membership facilities that sour talents from other members rather than from other members outside the region. AI-driven insights illustrate the main challenges, what skills are most needed and what geographical locations can be sourced from outside of the Baton Rouge talent.
We are also working with Beamery, a leading talent management platform, to align real-time labor market data with Beamery’s skill data. This allows HR teams to make better decisions in recruitment, workforce and succession plans. We also work with Joveo, an AI-LED job advertising engine, to present insights that organizations need to make accurate and accurate job descriptions.
Workforce diversity has been a welcome result of our work in helping organizations with skills rather than role sources. In the case of an airline, we helped them determine the engineering skills they needed to recruit and then look outside the aviation industry to attract applicants from the automotive world. Our AI-derived data helps organizations reach an unexplored talent pool, aligning more inclusive recruitment strategies with DEI goals.
How can companies mitigate the potential risks or limitations of relying heavily on AI for talent analysis?
One potential risk is overly relied on unsupervised AI, which can lead to biased decisions if the underlying data is incomplete or biased. To mitigate this, our consulting firms include expertise from across human resources so that we can fully combine data-driven insights with human expertise to be found in our workforce conversion solutions.
How do you see AI reshaping the concept of workforce agility over the next decade?
AI will continue to increase workforce planning and enable organizations to respond more agilely to market demand. As AI continues to become more complex, it will more effectively empower businesses to predict market disruptions and determine the right skills approach. Organizations will be able to decide whether they need to “buy” skills from the outside, “build” skills from the inside, “borrow” skills to fill temporary gaps, or combine methods that fit their context. With AI, the data needed to make these decisions can be prepared and available.
Thanks for your excellent interview, and readers who hope to learn more should visit TalentNeuron.
