AI is rapidly transforming how we work, but talent acquisition can often be left behind, missing out on the full potential of AI. In Radancy’s latest webinar, Building Talent Intelligence Architecture: Beyond AI Hype to Strategic Ecosystem Design, Jahkedda Akbar, Radancy’s SVP of Insights and Innovation, and guest speaker Betsy Summers, Principal Analyst at Forrester, explored how to move beyond the hype and build a connected, data-driven talent intelligence architecture.
AI is Transforming Work at Every Level
AI is reshaping every aspect of work, from how it’s done to who does it. According to Summers’ insights from the webinar, Forrester reports that 79% of global AI decision makers say that AI will impact employment planning over the next two years.
“AI, being such a powerful technology and tool,” said guest speaker Betsy Summers, “[is] going to change how work gets done, what work gets done, who does that work [and] how we experience the work.”
According to a Harvard Business School (HBS) leadership survey in 2023, 98% of organizations were undergoing a digital transformation, signaling an “always-on” strategy to changing business models. The pandemic accelerated this shift, forcing employers to rethink business models and talent needs. In Akbar’s words, “You go from bricks and mortar to e-commerce, and you’re reshaping what your workforce looks like and, as a result, the type of talent you’ll need.”
However, if work is changing so dramatically, why aren’t talent processes keeping pace?
The Talent Gap: Unevolved Processes
Despite widespread digital transformation, hiring processes have remained largely unchanged. The same HBS study found that recruitment practices, performance reviews and internal promotions were the least changed activities during organizations’ digital transformation. Not only that, but Radancy’s own survey revealed that talent acquisition is often excluded from AI task forces, with only two out of 18 talent leaders surveyed reporting being involved. Additionally, only 3% of talent teams report advanced AI adoption.
Image shared by guest speaker, Betsy Summers, Principal Analyst at Forrester
This disconnect creates risk and missed opportunities for hiring teams. Betsy Summers was surprised at the data from Forrester, stating, “It was a speechless moment for me when I saw that data. I just could not believe that in the midst of changing how work gets done … we are failing to also change … how we hire people, and how we are evaluating their performance and how we’re promoting people.”
To close this gap, we need to redefine what talent intelligence means.
Redefining Talent Intelligence
As AI drives change, how we define talent intelligence is still underdeveloped. Historically, talent intelligence has been narrowly interpreted and reduced to labor market data or basic skills matching. Betsy Summers emphasized, this definition is no longer sufficient.
She stated, “Even a couple years ago, we saw talent intelligence more aligned to labor market insights. But over the last two years, we’ve shifted to a more holistic understanding … looking at skills, knowledge, interests, aspirations and capacity.”
The Future of Talent Intelligence with Radancy
In discussing Radancy’s proprietary data, Jahkedda Akbar added, “There’s a massive opportunity to think about end-to-end data across the entire candidate journey, rather than siloing it in systems.”
Radancy’s platform leverages more than 670 million candidate engagements to surface insights that go beyond resumes. These engagements connect motivations, behaviors and job interactions to build a richer talent profile. Expanding the scope of talent intelligence enables smarter workforce planning, better retention and more personalized career development, laying the foundation for AI-powered transformation.
The Candidate Journey: A Source of Untapped Insight
Understanding the candidate journey is crucial for building an effective talent intelligence ecosystem. The candidate journey is a dynamic and data-rich experience. From job discovery to offer acceptance, candidates interact with multiple systems, each generating signals about their interests, motivations and pain points.
During the webinar, Akbar expanded on Radancy’s capabilities, saying, “At Radancy, when we have candidates coming to our customers’ Career Sites, we actually have an always-on survey … constantly discovering how motivations are ebbing, flowing and changing.”
These insights, captured through behaviors, preferences and emotional touchpoints, can inform everything from job content to engagement strategies. Job descriptions themselves contain embedded data about skills, seniority and team structure. When candidates interact with that content, they’re telling you what matters to them.
By connecting these touchpoints across the journey, employers can move from reactive hiring to proactive engagement, improving experience and fit.
The Recruiter Journey: Complexity Behind the Scenes
Hiring teams are navigating complex workflows, balancing speed, personalization and strategic alignment across fragmented systems. While technology has helped to simplify tasks, true transformation requires a shift from efficiency to effectiveness.
“Efficiency should be table stakes.” Akbar said, “If I’m putting in technology, whether it’s in my home or anywhere else, the assumption is it should make a process more efficient. But moving from that to really thinking about effectiveness is the hard work.”
Recruiters spend 6-35 hours a month per requisition on tasks like intake meetings, sourcing and scheduling – often using spreadsheets alongside tech tools. This approach limits visibility and slows decision making. Mapping the recruiter journey uncovers pain points and operational bottlenecks that AI can help address.
The DARE Framework: A Practical Guide to AI Opportunity Discovery
Once candidate and recruiter journeys are mapped, the next step is identifying areas where AI can create a meaningful impact. The DARE framework offers a structured way to evaluate and prioritize AI opportunities across the talent acquisition workflow.
DARE Framework:
- Data Availability: Is there structured, reliable data to support the task?
- Automation Readiness: Can the task be consistently executed through repeatable steps?
- Relationship Criticality: Does the task require human interaction or emotional intelligence?
- Economic Impact: What is the time, cost or volume burden of the task?
By scoring tasks across these dimensions, hiring teams can categorize initiatives into Quick Wins, Strategic Investments, Easy Experiments and Avoid/Delay.
This framework shifts AI adoption from reactive experimentation to intentional strategy, ensuring the technology supports both recruiter efficiency and candidate experience.
AI in Practical Application
Our webinar showcased several innovations that demonstrate how AI can elevate both candidate and recruiter experiences by performing tasks that weren’t possible before.
Natural Language Career Site Search
Candidates expect search experiences to mirror how they think and speak. Radancy’s natural language search enables users to enter full-sentence prompts, surfacing job content and insights tailored to their goals. 84% of Radancy users surveyed rated the AI search experience as “much better” or “somewhat better” than typical career sites.
Predictive Sourcing Agents
For hiring teams, Radancy’s sourcing agent uses predictive analytics to forecast performance and execute campaigns across channels. Recruiters can initiate campaigns with natural language prompts and receive real-time projections.
This tool shifts sourcing from reactive execution to intelligent orchestration, giving recruiters the insights they need to plan with confidence.
AI-Powered Job Summarization
Job descriptions can be dense and inconsistent. With Radancy’s AI summarization, candidates can extract key details, like skill requirements, responsibilities and benefits. This makes it easier for candidates to determine if they’re the right fit for a role. Radancy found that 74% of users wanted AI to extract key job components.
Radancy: Delivering the Future of Talent Acquisition
Digital transformation is already impacting how organizations attract, engage and hire talent through AI. However, success depends on more than adopting new tools. Employers need a strategic approach to talent intelligence, grounded in data, aligned with business goals and designed to elevate both candidate and recruiter experiences.
Radancy is leading this shift by delivering the future of talent acquisition. With natural language search, AI job summarization and predictive sourcing, the Radancy Talent Acquisition Cloud, powered by Agentic AI, helps organizations build talent ecosystems that offer real value.
Watch the full webinar to hear how hiring teams can transform their talent acquisition strategy with AI. Connect with our team to see how Radancy can help simplify your hiring, reduce costs and build the workforce of tomorrow – book a demo.
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