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Capital H blog

Cognitive and AI technologies are transforming talent acquisition

July 2, 2019

How ready are you to take advantage of them?

More and more we are seeing organizations augment their applicant tracking system (ATS) with AI technologies to enhance recruiting efficiency and effectiveness—for example, AI-enabled web crawling for sourcing; chatbots for screening; machine learning for candidate ranking and fit. The operating model is being adjusted for the AI technologies being adopted, and the role profile of the recruiter is changing to accommodate these technologies.

Assessing your organization’s readiness to adopt these technologies is a crucial first step, as discrepancies in readiness can create issues. For example, if an organization is financially ready to adopt a cognitive tool, but its recruiters are not ready to use them, the true value of the investment will not be realized. Assessing readiness before jumping in helps assure alignment within the organization in how the tools are used, prevents unforeseen roadblocks, and lays the foundation for long-term success.

Readiness can be determined by factors such as business need, infrastructure, leadership buy-in, budget availability, technical skills, and governance. Depending on these parameters, you may be at any one of three levels of readiness: foundational (low), operational (medium), or transformational (high). Understanding the nuances in the requirements and competencies within these readiness levels will support the organization’s ability to implement and use AI technologies effectively.

All TA organizations start on the same foot with low levels of readiness, but should strive and take necessary steps to reach a high level of readiness, where AI technologies can be transformational for the TA function. The levels are cumulative: the highest (transformational) level has all the characteristics of the two lower levels.

At what level is your organization’s readiness?

Foundational (Low): You are interested in the use of AI and have a budget to spend, but have not connected this well to your overall TA Strategy.

Key characteristics:

  • A clear business need: This could be evidenced by too much time spent on repetitive, administrative or transactional tasks, a need to enhance the candidate experience at higher volumes or limited work incorporating AI technologies into the TA operating model. AI technologies can free up recruiters’ time so they can be more strategic in their role, and deliver a consistent candidate experience.
  • Basic infrastructure: Core recruiting data is in place (job aids, job descriptions, position management, maybe even a workforce plan) and representative pools of candidate data are available.
  • Resources: Basic TA leadership buy-in has been secured in the form of funding availability. Budget may be low, but it is clear, with an outline of both hard costs (such as purchase price) and soft (such as efficiencies gained and higher quality of hires).

Operational (Medium): You understand AI and have invested time to understand this market. You are driving results in candidate flow but are struggling to tie to this to business outcomes.

Key characteristics:

  • Effective delivery capability: Ability to gather requirements, maintain databases, and build and test continuously. This is critical because AI solutions are not a one-and-done solution but an evolving solution that gets better with more data, time, and corrections.
  • Technical skills: Availability of solutions architects with both AI know-how and knowledge of the TA organization, as well as an internal IT function that can support the implementation team.
  • Governance: Ability to evaluate the risks of AI solutions and minimize potential negative impacts to candidates and the business, but business impact is not fully understood.

Transformational (High): You are invested in the use of AI as the system of engagement with your candidates and understand how this is driving business value that was not available previously.

Key characteristics:

  • Broad and aligned leadership buy-in: TA, HR, and organizational leaders see AI technologies as strategically integral to the organization’s ability to compete in the talent market and consider it an opportunity for growth.
  • Optimization: TA realizes the value and reaps the benefits of the AI solutions that are implemented. For example, the candidate experience is woven together with the technologies and supports the employer value proposition.
  • Business acceptance: From TA leaders to sourcers to hiring managers, the AI solution is accepted and being used in daily recruiting activities to drive outcomes.

Readiness drives value
Readiness for AI is not the same as being able to benefit from AI—every organization can potentially benefit from AI. Immature and highly transactional TA functions may benefit the most because of the efficiency gains AI makes possible, but even mature, optimized TA functions can still realize greater efficiencies. The level of readiness for AI does, however, impact short- and long-term value. Organizations at the highest, transformational, level of readiness are positioned to realize the greatest value.

Bhawna Bist is a senior manager in the Workforce Transformation practice of Deloitte Consulting LLP, specializing in HR & Talent Acquisition Transformation. She has more than 16 years of cross-industry and consulting experience advising global organizations and leads the development of the firm’s point of view around AI in TA.

Alice Jun is a consultant in the Workforce Transformation practice of Deloitte Consulting LLP. Alice has focused on Talent Acquisition Transformation and supports the development of the firm’s perspective on AI technologies.

Originally published at Capital H blog