AI promises to deliver a powerful and versatile new set of capabilities with the potential to drive transformative change for organizations. John Brownridge, principal, and Greg Vert, senior manager at Deloitte Consulting, explore how AI is already impacting the workforce today and how it will continue to shape future strategies.
As adoption increases, the impact AI will have on future workforces is starting to come into focus. AI and other technological advances significantly impact and shape the future of work. Organizations have started to adopt and experiment with AI, and the early learnings are helping to forecast the impacts this innovative technology will have on the workforce when fully proliferated and embedded in the way work gets done.
AI Disrupts the Workforce in Different WaysÂ
There are three primary applications of AI in practice: automating complex tasks and end-to-end processes, creating intelligent and guided digital experiences, and analyzing large and fragmented data sets to unlock insights and create new outputs.Â
Each of these applications of AI will have different and direct impacts on the workforce. Automating tasks and processes can help reduce work and create capacity within organizations. In many cases, automation at scale will trigger the need to re-architect jobs and functions. Creating better digital experiences will likely make workers more productive and create capacity, which organizations can use to help reduce the overall burden of work and improve the well-being and engagement of the workforce. Finally, unlocking insights and creating new outputs will likely give workers higher quality information in real-time to augment decision-making and improve deliverables, increasing the effectiveness of the workforce.Â
The cumulative effect of all three applications working together can help create transformative workforce change. Let’s take an illustrative example and assess the combined impacts of AI on a Financial Analyst role. For purposes of this exercise, estimate 50% of the Financial Analyst job can be wholesale automated with AI. The work, such as aggregating data and building standard reports, is eliminated and no longer requires human intervention. Out of the remaining 50% of the job, an AI-powered Digital Assistant could make the Analyst 2x more productive by scheduling meetings, collaborating with team members, and completing administrative activities in backend systems on the worker’s behalf, such as entering time off and processing expenses. The Financial Analyst becomes more effective with AI providing better, on-demand insights to reduce rework, increase turnaround time, and improve performance. The end result for an organization is the potential to yield more value by investing in a 0.25 full-time equivalent (FTE) paired with AI as part of a â€œsuper teamâ€ compared to 1.0 FTE with no AI support. When you scale this type of approach across the entire Finance function or enterprise, the workforce gets leaner, more focused, more productive, and more effective while AI plays an increasingly extensive role.Â
However, many organizations are not pursuing AI as a way to reduce headcount â€“ at least not as the primary objective. In the 2020 Deloitte Human Capital Trends ReportOpens a new window , 64% of respondents viewed AI as a way to oversee or assist workers, and 66% expected a net increase or the same number of jobs, but with changes to the work performed. Organizations should anticipate the gradual elimination of work and disruption of traditional jobs and functions over time, but it doesn’t necessarily equate to an overall workforce reduction. The areas of work ripe for disruption are high volume and repetitive or rules-based activities, â€œwork about workâ€ or the activities not directly tied to how an organization generates value, and activities that machines are generally better suited to perform, such as large-scale data analysis and pattern detection. But as traditional work is disrupted, there are a variety of new skills and jobs emerging to architect, deploy, and support AI.Â
AI Demands New Skills and Teaming Approaches
Organizations are struggling to harness the full potential of AI, in part, because they lack the required human talent and have not shifted to new ways of working. It takes multi-disciplinary skillsets and teams to integrate AI across an enterprise. To deliver AI solutions effectively, there is a need to bring together diverse talent pools, including product managers, UX specialists, solution architects, data scientists, functional and process experts, technical developers, and many others. Many of these skillsets are both scarce and in high demand at the same time, which creates a significant barrier for many AI programs to succeed. Even with the right talent mix, organizations also need to shift to more agile and product-focused delivery models to deploy iterative solutions, otherwise, it could be a challenge for AI programs to get started, to demonstrate value, or to scale.Â Â
There is a golden opportunity for organizations in the early stages of adoption to proactively develop a talent strategy to support the transition to the AI-enabled future of work. The strategy should be comprehensive and include direction on how to acquire, develop, deploy, support, and reward the workforce of the future for driving and enabling the enterprise AI strategy. For example, some organizations are overcoming the talent gap by reskilling and redeploying workforce segments disrupted by AI. Many of the required disciplines, such as product management and UX, can be learned by existing team members with core business acumen and delivery and analytical skills. Organizations should consider investing in the training programs, on-the-job experiences, and career pathways to help potentially displaced workers develop these new in-demand skills and move to new roles. It is a potential win-win for workers and the enterprise and can reduce the amount of external hiring or contingent worker spend required to deliver AI programs. The challenge will be creating the capacity and incentive for workers to build the AI solutions that might ultimately disrupt their current role. It is important to align the deployment and rewards part of the talent strategy and effective change management.Â Â
Many AI solutions also offer low code / no code deployment approaches to allow business users and other non-technical resources to contribute to implementing and expanding AI capabilities. Democratizing AI and putting it in the hands of existing team members with functional and process knowledge is a powerful way to mitigate tech talent shortages and accelerate solutions delivery. With the right governance in place, this type of â€œcitizen developerâ€ model also allows subject matter experts to elevate their role from firsthand execution to orchestrating an AI team to get work done.Â
In addition to the talent strategy, organizations are shifting to a product approach to deliver and manage AI programs. The product mindset applies agile practices to focus on rapidly delivering AI solutions that create specific, measurable value for workers and the enterprise. The approach uses insights to embrace continuous improvement opportunities to ensure AI products remain valuable over time. It also means teams are working on shorter cycle sprints to deliver iterative solutions with the goal of experimenting, collecting feedback, and refining over time. Successfully making the shift to the product approach will require new skills and roles and should be incorporated into the talent strategy.Â
Creating the AI Workforce AdvantageÂ
Many experts have argued that AI is inevitable, but the reality is that it requires humans to find applications and to develop and manage the solutions. The inevitable part â€“ is that the organizations and workforces that evolve to thrive in the future will undoubtedly have AI as a core part of their success. HR, technology, and business leaders have an opportunity to accelerate this evolution and create a competitive advantage by establishing the AI vision, strategy, and roadmap inclusive of the cultural, talent, and operational shifts required. As with most things, technology alone will not generate transformative change. The ability for organizations to successfully navigate the human capital challenges could make all the difference.Â
What AI trends do you see shaping the world of work in the coming years? Tell us on LinkedInOpens a new window , TwitterOpens a new window , or FacebookOpens a new window . We’d love to hear from you!