From Customer Journeys to Candidate Experience: The impact of AI

At Acorel, we’re at the forefront of implementing SAP CX solutions that are transforming how businesses interact with their customers. As artificial intelligence is revolutionizing various industries, the SAP (CX) landscape is no exception. With SAP’s new generative AI capabilities (like AI copilot Joule), the SAP eco-system is becoming ready for a future where data-driven decision-making and intelligent automation are the keystones of business innovation.

But it’s not just customers who benefit from these advancements in AI-driven experiences: even as a recruiter, I’m still impacted (and very much fascinated) by the continuous improvements made in AI. Its enhancing professional life in every field by making work faster, more efficient, and more insightful, allowing for deeper analysis and strategy. Within the recruitment landscape, this translates into tools for crafting personalized emails, smarter applicant tracking, and predictive matching to find the ideal candidate fit.

As I did in my last blogpost, I like to draw some comparisons between Customer Experience and Candidate Experience. So, let’s look at how AI has impacted both and what we can learn from it. Drawing parallels between customer and candidate experiences reveals some key insights:

• Personalization: Both customers and candidates value experiences tailored to their needs. Just as personalized marketing increases engagement, personalized communication in recruitment creates stronger connections with potential hires.
• Efficiency: It is now easier than ever to implement chatbots, automate interview scheduling, or create tools (without technical knowledge) to screen and filter through resume’s. AI enhances efficiency in handling tasks and data, but the quality of personal interaction remains essential for both customer and candidate experience. The balance a company strikes between automation and a personal touch reflects its culture and brand ethos. This means it needs to be taken into careful consideration.
• Predictive Analytics: In Customer Experience, predictive analytics is used to anticipate purchasing behaviors. In the Candidate Experience it can be used to forecast candidate success and company fit.

However, there are also major differences between the two experiences:

• Interaction Frequency: Customers often engage regularly, thus are providing more data. This in turn lets AI focus on long-term behaviour tracking and loyalty building. With candidates who engage only sporadically, AI focusses on immediate suitability instead.
• Data Sensitivity: AI in recruitment handles more sensitive personal data, requiring more strict privacy measures compared to customer experience AI.
• Outcome Objectives: AI in Customer Experience aims to drive sales and customer satisfaction, while in the Candidate Experience the goal is to enhance fit, alignment, and retention.

These distinctions show that while AI’s role in both customer and candidate engagement shares a common ground, the nuances of each journey require different approaches.

A careful balance is necessary in both situations, but particularly when taking the candidate’s expertise into account: The degree of automation and AI integration used by a business should be consistent with its core principles and the employer brand image it wants to present. In a digital startup that wants to expand rapidly, more AI might be used to help sort through various jobsites to source talent, or be integrated in their entire hiring proces. A family-owned business, however, might only employ automation and AI for a very limited number of activities in their hiring process to ensure everything stays personal and authentic. Considering the company’s growth goals and brand, the choice of how to apply AI should be a strategic one.

In the end, as we see in all the fields where AI makes significant advances, it’s not about replacing the human touch but rather complement it.