Why humans are the essential factor in the success of Artificial Intelligence (AI)

Why humans are the essential factor in the success of Artificial Intelligence (AI)
Aon Insights Series Asia

04 of 05

This insight is part 04 of 05 in this Collection.

November 8, 2023 7 mins

Why humans are the essential factor in the success of Artificial Intelligence (AI)

Why humans are the essential factor in the success of Artificial Intelligence (AI)

How AI is transforming data and analytics in the workplace.

While Artificial Intelligence (AI) offers powerful tools to shape data-driven decisions across human capital, its success hinges on a crucial element – the human touch. An effective AI integration relies not only on technology and data, but also the strategic insight, creativity, and enthusiasm of your people.

Building the foundations of a successful AI capability

AI represents a leap forward in technology’s ability to problem-solve with less human intervention. This can set up an assumption that having the right data and technology available will result in less need for human resources – in the HR function itself and across organisations as a whole.

While AI uptake can certainly bring major time savings to HR tasks and processes, it requires HR leaders and teams to lead the human effort AI adaptation demands. This includes a cultural shift from the idea that AI will replace employees towards having a workforce that can feel enthusiastic about AI as a value-add to their experience at work. Developing AI literacy is also essential if employees and teams are to maximise the benefits of AI in their own work, and partner effectively with internal experts and vendors on AI integration.

From organisation-wide transformation to project-by-project implementation, bringing people on the journey is key to success and innovation. This is why HR have a critical role to play, both in setting an example through their own adoption and working with executive leaders to establish the guardrails for proper and effective AI governance.

AI is an opportunity for HR to enhance, not replace, HR skills

During the inaugural Aon Human Capital Innovation Symposium, Rachna Sampayo, SVP of Human Resources for Japan & Asia Pacific at Oracle, discussed how generative AI can enhance existing data and capabilities to accelerate ‘manual’ processes. She has experienced how this approach can create the immediate efficiencies for HR teams to deploy resources more effectively, improving both quality of delivery and freeing up time to focus on strategic priorities. “It is making an HR manager’s world more purposeful, more impactful because you don't have to be bogged down with administrative tasks,” she says.

Rachna described how using resume scans in recruitment means hiring managers and HR teams automate filtering of candidates and focus on a quality interview experience to improve decision-making. She also highlighted other opportunities for AI to support better outcomes for the HR function in supporting employee engagement and performance:

  • Enhance ‘listening’ capabilities to improve employee engagement programmes

    AI can interrogate results from multiple pulse, engagement and opinion surveys to produce sentiment analytics as the basis for intervention recommendations. This informs better decisions for employee programme design and investments that can target areas where your workforce is looking for improvements.

  • Simplifying job descriptions for clear expectations and improved performance

    By creating more succinct and consistent job descriptions, AI can provide employees greater clarity on what they are expected to do in their role. This sets up a clearer framework for goal-setting conversations, supporting more productive outcomes for individuals and teams.

AI literacy is key to capturing the power of AI and recognising risks

Rachna is quick to point out that this integration hasn’t happened overnight. “For the last two years we’ve been building the digital capability in our HR team so that every person, no matter whatever their role, has a level of digital capability and data numeracy,” she says. “This enables them to be more intentional in how they use AI in the work they produce.”

Rachna considers her team to have moved to ‘DigiHR 2.0’ as they expand their skillset to match the growth in opportunities to use AI in HR. This higher level of AI literacy becomes critical not only for AI take-up but also for the responsible use of AI. Humans act as an essential layer to counter the risk of AI introducing error and bias into decision-making by having knowledge and awareness in the following areas:

  • Review competence

    “We need human experts to discern whether the outputs from AI are accurate and consistent with their worldview,” Symposium panellist Professor Damian Joseph from Nanyang Technological University said. “This is a skill which needs deep domain expertise and experience.”

  • Over reliance on AI

    Professor Joseph also shared insights on the potential for over-reliance on AI from his research into machine learning on the potential for over-reliance on AI. “There is the danger that employees may abdicate their decision to the AI,” he says. “This over reliance leads to less thinking and a more routine approach to using AI in their work.”

  • Managing and mitigating bias

    “One of the key aspects when we are looking at AI literacy uplift is to help our workforce understand the kind of the biases embedded in some of the training data for machine learning” says Emily Yang, Head of Human-Centred AI and Innovation – Strategy and Talent at Standard Chartered. “If societal and cultural biases get perpetuated into algorithms, it introduces, for example, possible risk of inaccuracy from biases such as but not limited to gender bias when matching resumes to occupations and roles.”

Effective AI literacy needs to encompass skills and structures

Data and analytics and AI-driven programmes come with risk but there are policies, processes and structures organisations can introduce to support successful outcomes. During the symposium our panellists highlighted the value of robust vendor management and data audits as two examples of measures that can set people up to manage risks coming from AI in HR and organisation-wide functions.

“Having a meaningful conversation with your developers or with a third-party vendor means making sure they share a fairness assessment or other technical documentation to show that steps have been taken to release an AI system that is responsibly developed in mitigating bias in the AI data,” says Yang.

Rachna discussed the value of implementing safeguards against bias in data and over reliance on AI. “You need regular audits of your machine learning and your advanced analytics to make sure that it’s set up for fairness and objectivity,” she says.

Upskilling people to get the best from AI in the workplace

Giving proper consideration to roles and skills can help organisations unite human expertise with AI technology. It takes training, as well as changes in culture and governance to create a robust framework for innovation, such as layering generative AI onto existing data and analytics tools to power up informed and strategic decision making.

Just as people can unlock the potential of AI, so AI can unlock the potential of people to be more productive, deliver greater value from their work and have a more rewarding experience in the workplace, both from being more successful in their own role and being part of a more successful organisation. “As long as we are using it wisely and we're using it for the right reasons, I think it is definitely making life easier,” says Rachna.

A higher level of AI literacy becomes critical not only for AI take-up but also for the responsible use of AI. Humans act as an essential layer to counter the risk of AI introducing error and bias into decision-making.

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This document is not intended to address any specific situation or to provide legal, regulatory, financial, or other advice. While care has been taken in the production of this document, Aon does not warrant, represent or guarantee the accuracy, adequacy, completeness or fitness for any purpose of the document or any part of it and can accept no liability for any loss incurred in any way by any person who may rely on it. Any recipient shall be responsible for the use to which it puts this document. This document has been compiled using information available to us up to its date of publication and is subject to any qualifications made in the document.

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