Shot of a young businessman and businesswoman using a digital tablet during a late night at work

How artificial intelligence can augment a people-centered workforce

AI is disrupting approaches to talent strategy, risk and resilience. It’s crucial to blend operational gains with a people-first mindset.

Two questions to ask

  • How does your digital strategy encourage human connections?
  • How will generative AI and other technologies evolve and adapt your organizational culture and employee experience? 

No matter the workforce tools, it’s people who are ultimately visioning, building, and experiencing the seismic shifts in the status quo of work. Chances of sustainable business and capability growth hinge on whether organizations keep a people-first mindset while integrating new technologies.

The ability of generative artificial intelligence (AI) to convert user input into valuable deliverables — custom code, data analysis, drafts of reports — is big business. Forrester estimates spending on AI software will reach US$64 billion by 2025, during a turbulent time when digital transformation is converging with labor market, economic and geopolitical uncertainty. Each challenge requires organizations to think of multidimensional business strategies that maximize efficiency, minimize cost and risk, and cultivate a future-ready workforce.

No single tool or solution can address the myriad changes, challenges and potential opportunities facing the modern workforce. As organizations refine their approaches to flexibility in how and where work gets done, they also need to upskill, reskill, attract and retain the right people amid an evolving and long-running race for talent. Organizations need to deploy the most efficient tools and processes to create sustainable value while still investing in the skills, career and personal growth of the workforce to create a more exceptional employee experience.

To realize the full potential of generative AI — or any technology — organizations need to bring a holistic, people-centered perspective to an increasingly more digital world of work. Instead of just focusing on the capabilities of generative AI, it’s important to consider how its use might enhance both the operational and experiential realities of the “next normal” of work.

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Chapter 1

Reimagining digital work

Generative AI has the potential to disrupt how work gets done, but that potential should be paired with clear purpose.

The ability of AI systems to enhance the experience of work is already rippling through the budgeting, hiring and operating strategies of global businesses. According to the World Economic Forum’s Future of Jobs Report, businesses are anticipating sustained labor market churn with an increasing focus on AI investment and the potential for automation. Respondents expected a 23% churn in jobs over the next five years between the creation of new roles and the reduction of others. The highest growth job categories in relation to their size today are technology related, with AI and machine learning specialists at the top of the list. 

Respondents expect a
churn in jobs over the next five years.

This corresponds with findings from the EY 2023 Work Reimagined Survey, where 84% of employers say they expect to have implemented generative AI within the next 12 months. This expectation is paired with a generally positive sentiment around the technology, especially as it relates to new ways of working. Of both employee and employer respondents to the survey, a net positive 33% see potential benefits for productivity and new ways of working, with a net positive 44% seeing benefits to the reality of flexible working. 

Net positive sentiment of
see potential benefits for productivity and new ways of working.
Net positive sentiment of
see benefits to the reality of flexible working.

For employees, this positivity may be connected to the potential of generative AI rather than experience with it, as just 49% of employees are using or expect to use the technology in the next year. 

While the potential of generative AI may have largely broken into the wider mainstream relatively recently, this disruption is a chapter in a broader reimagining of the realities of digital work. Just as with the growth in capability and availability of tools and processes for remote and hybrid working, generative AI may fundamentally change how work is done, while also influencing the experience of work.

Importantly, this deeper integration of AI into the world of work doesn’t mean a wholesale replacement of people because of AI. Instead, there is likely a percentage of tasks for every employee that might be supported by AI tools, building an organization’s capacity while better equipping employees. AI might present a first draft of a piece of work, but it’s well-trained and trusted people who make final decisions. People are then freed to focus on higher-value tasks, fueled by innovation and creativity.

Sustainable value doesn’t come from technology itself, but from what people accomplish with it. 

Still, it’s difficult to realize the full potential of these tools without clear purpose. Adopting technology just for technology’s sake carries inherent risks: new technology plus an outdated process will only equal an expensive old process, creating a subpar experience for employees and customers. The more sustainable value of technology adoption doesn’t come from what the technology does, but what the user can do with it.


With this in mind, we can plot the potential impact of generative AI in two powerful categories of use cases: AI collaboration and talent and governance strategy.


AI collaboration


Organizations will have to assess how AI could influence both back-office functions, and customer-facing work. For example, AI might be thought of as an added digital assistant taking on bulk analytical or technical tasks in a first instance. Employees could utilize their AI tools for mundane or repetitive tasks. The Digital Worker Experience Survey from Gartner found that 47% of digital workers struggle to find the information or data needed to effectively perform their jobs, presenting an opportunity for AI-powered tools and collaborative technologies to increase efficiency.


More wide-reaching for internal use is generative AI’s influence across business functions, like HR and  Payroll (via US). AI tools can perform rolling analysis on performance indicators of employees and recommend training and upskilling opportunities. Through individualized credentials and authentication, AI tools can give different levels of information appropriate to the seniority and job title of the requestor. These digital tasks can run independently, around the clock, allowing for reports or red flags to be delivered constantly. This is more robust than traditional automation because these new tools have deeper context and generative abilities.


Talent and governance


Generative AI’s ability to identify training opportunities for employees can also contribute to an overall assessment of the skills organizations have now and will need in the future. The ability to customize these technologies can enable new ways to create a career development track attuned to employee experience and business need.


Importantly, the enterprise-level implementation of generative AI with large data sets and confidential materials can help ease compliance exercises, while also creating areas for potential risk. These AI tools built for purpose can automate the gathering, cleansing and interpretation of data, while summarizing findings and offering recommendations from it. These tasks need to be done within the context of an organization’s ethical AI governance framework, maintaining guardrails that are appropriate for an organization’s particular needs. Generative AI outputs should be seen as first drafts, with people making adjustments and final assessments of the work.


But appropriate guidelines can make that first draft even better.


For business functions requiring bulk retention of certain types of data to maintain regulatory compliance, or more stringent privacy controls, generative AI tools need to follow clearly defined and transparent access and retention policies and have processes in place to monitor for potential legal risks around the use or leveraging of intellectual property.


This need extends to AI-enabled HR tools to assess opportunities for improvements to internal communication, process change or technology investments, or other unseen challenges. By mixing quantitative and qualitative assessments of the workforce, both with AI tools and apart from them, leaders can better understand the state of organizational culture and capabilities. Industrializing the analysis of multiple data sources may help identify bright spots or hotspots related to employee retention, and quickly, deeply and consistently respond to and anticipate opportunities.


Similarly, this assessment can flag potential compliance or regulatory risks in real time. But the effectiveness and reliability of this activity relies on an appropriate ethical generative AI framework and governance model, including countering potential bias transmitted through public training data, and avoiding the recycling of toxicity received in certain inputs.   


Even with the need for regular management and maintenance of generative AI tools, these systems can provide better visibility on how an organization is operating and organizing itself for the “next normal” of work.

Multiracial business team team at rooftop in contemporary modern office talking, planning and thinking strategy. Corporate businesspeople discussing business strategy at night, urban balcony overlooking city, Liverpool, London. Holding digital tablet.

Chapter 2

AI, authenticity, and employee experience

People are the ones using technology. Organizations should keep the human experience of work at the center of generative AI implementation.

As exciting as generative AI may be in reimagining work, its potential can only be realized by the people who use it. Achieving that potential also rests in expanding the capability that we each have inherently with new tools, with better-connected insights, and with rapid delivery of them, while not losing our humanity in the process.


This embrace of new technologies should be considered part of a constant state of digital transformation, whose chances for success are tied closely to how well the emotional and rational concerns of employees are addressed and respected. A more thoughtful approach to generative AI integration can lead to more positive influence on the overall employee experience.


All employees are influenced by their use of technologies in their personal lives — ecommerce, consumer interaction, access to information — that creates an expectation in the workplace, and that expectation can differ drastically between generations. Younger employees are more comfortable blending their physical and digital lives, seamlessly shifting between interactions and activities online and in-person without as much of a separation of the two. This combined with Gen Z placing a high value on authenticity, transparency and integrity (via US) in their interactions presents an important consideration for generative AI’s implementation and influence on talent retention and attraction.


All of this points to the fact there isn’t a one-size-fits-all approach to technology adoption. Younger employees may be afforded more AI-enabled self-services, for example, while more training and effort at acclimation might be offered for employees less comfortable with new tools.


Technology ultimately has a major role to play in how we think about ourselves and operate in the workplace and outside of it, and balancing our tendencies and needs in a thoughtful way will promote an employee experience that attracts and retains valuable employees. The EY 2023 Work Reimagined Survey shows just 17% of employees and 22% of employers are prioritizing training in generative AI-related skills in 2023, ranking far below a desire for better training to improve remote working skills and tools, the top priority for both employees (41%) and employers (52%). Even if the skills focus now is more on improving the overall experience of work, increased deployment of generative AI tools will increase the need for people to be able to use it.


Organizations should consider approaching generative AI with a balance of appreciation for its role in a comprehensive workforce strategy, and awareness of the potential challenges which may be ahead. Here are four areas of focus:


Assess how generative AI can empower your people

It’s important to understand how generative AI might best fit within your organization, and how that implementation might create opportunities and risks for your operations and people strategy. Generative AI tools can create first drafts of interpretive reports or analysis, saving time and energy for employees to focus on final assessments and steps forward. Generative AI can play a similar role for organization-wide talent considerations, influencing talent acquisition, onboarding, performance management, learning and skills development, and more.


Explore potential risks and security concerns

Any implementation of a powerful technology like generative AI creates the potential for risks that should be considered and mitigated. These risks can be directly related to the technology itself, for example having appropriate regulatory, compliance, cybersecurity and privacy guardrails in place for generative AI tools to access disparate data sources. Processes should also be created to account for accuracy and reliability concerns with generative AI outputs. Risks may also stem from how well integrated generative AI systems are in countering bias and reflecting your organization’s diversity, equity and inclusion (DE&I) strategy. Similarly, organizations should gauge potential resistance to generative AI from employees, and assess what further actions may help support positive organizational culture.


Consider size, scope and cost

Generative AI systems can be bespoke, requiring a decision of which model of generative AI is fit for purpose. This includes evaluating performance and cost trade-offs with considerations related to potential talent-related benefits. Organizations also need to evaluate their current and future knowledge-based infrastructure considerations for using generative AI tools, and design and build the large language model to enable the system. Part of this assessment phase can include the exploration of potential industry partnerships and alliances.


Chart the path forward with people at the center

Technology’s effectiveness ultimately depends on how people use it. Organizations should develop a comprehensive roadmap for how your people will be trained to use new tools in a way that helps them feel empowered to focus on higher value tasks. Implementing metrics that measure workforce sentiment tied to confidence in and adoption of the new technology, will help organizations adjust their strategy as necessary through the digital transformation. 


Generative AI is already disrupting how organizations think about how they create and offer sustainable value in an increasingly turbulent world. It’s not a question of when AI will affect how business is done, in any industry, but rather how prepared are organizations to maximize the technology for their clients and their employees, while keeping people at the center. The leaders who leverage this approach will be best positioned to realize the benefits of reimagining digital work in a responsible and sustainable way.

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