New tech. New work. Your old value case isn’t enough.

New tech + new work = new value case

Leaders are in a new normal. Instead of a few core technologies to choose from, they are faced with hundreds. Instead of a handful of use cases, they are presented with dozens—often in the same platform, with overlapping use cases across the board. Instead of single functional stakeholders and owners of technology, tech is now owned across multiple functions and stakeholders. And perhaps most importantly, many emerging technologies now enable organizations to create altogether new ways of working, instead of just enabling existing processes to be done faster or cheaper (figure 1). 

This change is happening everywhere, across all types of technologies. For our purposes, we are focused specifically on work and workforce technologies.

Work tech includes technologies serving as productivity, augmentation, and collaboration tools. These are technologies we use to do our work (e.g., spreadsheets, email, social collaboration tools, medical diagnostic tools, navigation tools, etc.) and new artificial intelligence technologies in which people and smart machines work together.

Workforce tech includes a dizzying array of systems that help organizations manage, grow, and develop their workforces (figure 2).

Leaders today must organize and orchestrate new technologies in a world where traditional boundaries between them are falling away. Sixty-two percent of respondents to our survey say this is critically important to their organizational success, yet only 28% are doing something meaningful about it (figure 3).

So what’s holding them back?

HR and IT leaders rarely have been pressed to consider so many shiny new objects. They have the tantalizing sense that certain technological advancements, particularly various manifestations of AI, could unlock enormous value—if they could just figure out which ones, gain enough clarity about the value to articulate it in a compelling business case, and implement it effectively.

Yet organizations may be jaded after watching previous investments in tech stacks fall short of expectations and fail to realize expected ROI. In fact, one Deloitte study found that only 50% to 75% of organizations believe they are getting value out of the major tech investments, such as enterprise resource planning, data architecture, and cloud platforms, and traditional and generative AI.¹

Based on these challenges, leaders are faced with difficult questions, such as:

• My team says this tech will be game-changing—but how do I make a business case when the benefits are hard to quantify?
• We have so many tools already. Do we really need a new one—or will it just cause confusion and frustration?
• Will this technology create lasting value for our business and our people—or is it just the latest shiny new object?
• Should we invest in new tech or hope our cloud platform providers eventually incorporate the functionality—and how do I assess the cost of investing versus waiting?

These questions demonstrate that some leaders are overwhelmed by their options and hesitant after previous disappointments that may lead them to feeling paralyzed.

Alternatively, leaders may feel pressure to act even in the absence of clear goals, a realistic appraisal of the ability to achieve them, or an understanding of the connections between those goals and larger business strategies. According to our 2025 survey, more than four in 10 organizations we surveyed (42%) cited unrealistic business cases or a lack of data to evaluate them properly as key reasons tech investments have fallen short. As a result, many leaders will sink considerable time and capital into buying and implementing new technologies, only to change direction later or realize they have invested in redundant technologies.

This changes the nature of the decision-making process. As technology’s role and potential impacts become more complex, so does the value case for it.

But failing to invest in technology threatens to undermine outcomes across multiple dimensions, including human performance, business performance, quality, expertise, brand, innovation, and the worker experience, potentially leading to loss of faith among workers, partners, customers, and investors.

To make effective investments in tech, leaders will need to navigate difficult tensions, including how to balance a focus on the immediate and predictable return of automation versus the potential larger value from augmentation use cases (figure 4). In addition, there is a tension between focusing on harder to quantify outcomes (e.g., innovation, capabilities) in the value case versus more traditional outputs (e.g., efficiency).

Finding the value in work and workforce technology

Given the tensions and challenges discussed above, most organizations will need a new approach to work and workforce technology and new metrics to measure the value these technologies are creating. How can leaders identify when their tech value case warrants a nontraditional approach?

Start by defining the intent of the technology. Some organizations graft the technology onto existing business processes without converting the work to account for changes the tech introduces.

Based on the intent, consider whether a traditional business case is sufficient for the goals you are pursuing and the technologies or other investments you are considering. You may need a different approach if:

• Your technology investments will reshape work. For example, AI-powered writing tools used to draft stories for media, job descriptions, policies, or legal documents for humans to review may alter roles and job design.
• The technologies are intended to magnify or improve human capabilities, not replace them. Next-generation workforce technology investments may elevate your workers’ creativity and ability to innovate, help them learn faster, enable them to tap and internalize your organization’s tacit knowledge, or provide value in a host of other ways that can be difficult to quantify.
• The investment case is probabilistic. Some next-gen technologies promise large payoffs if they work but present meaningful risk of failure.
• The technologies would have broad impact across functions. Certain investments may have implications across your organization, not just within HR or any other single department. For example, AI-powered collaboration tools (even relatively basic tools embedded in video and sharing platforms) tend to be broad in their value or impact.
• The time horizon is unclear. Can you anticipate a measurable payback in a year? Three years? Is it possible to know how long the return on investment will take?
• Success will depend on complementary organizational changes or investments. The more interdependencies there are between the investment and additional technologies or changes, the greater the complexity, the wider the potential range of outcomes, and the more you may need a more nuanced, holistic business case.

Once you’ve identified whether your organization needs a nontraditional approach to tech value, you can begin to develop the new metrics, new approaches, and new governance that will help ensure your tech investments are delivering value.

New metrics: Focus on business and human outcomes

Nearly three quarters (73%) of executives surveyed in Deloitte’s Mapping digital transformation value report said the number-one challenge to determining the value of tech investments was the inability to define metrics.²

Organizations evaluating technology may be applying outdated, too-narrow frames that fail to capture the quickly expanding range of ways technology can be applied. Deloitte research has identified a taxonomy of 46 key performance indicators related to digital transformation value. Organizations are using only a slice of them: Most of these KPIs are used by less than 55% of organizations surveyed.³

Consider the process for evaluating an investment in a productivity tool that saves every worker 30 minutes per week. The organization needs to decide how to attribute value to that time savings. If it applied the traditional technology investment mindset, it might sum the time savings across the enterprise, determine the number of full-time equivalent workers it works out to, and assume a commensurate reduction in head count. But that approach may not represent reality; it may be more germane and more valuable for the organization to consider the ways it could use workers’ additional 30 minutes per week to achieve other business goals, such as reducing burnout or stimulating innovation, and measure progress toward those outcomes.

For example, when one Fortune 100 food and beverage company sought to justify the value case of implementing a digital experience hub for its 300,000-plus global employees, the company needed a holistic business case that went beyond the traditional measures of productivity and cost efficiency. At its core, the company’s value case focused on three key pillars:

• Faster: Give time back to workers to focus on value-added tasks.
• Stronger: Reduce cost to serve, and enhance resilience and agility.
• Better: Improve the employee experience to increase engagement and retention.

While the first two pillars included typical metrics such as productivity and cost avoidance, they also included measures of “slack” for value-added work and enabling organizational agility. The company identified 2 million hours of time as part of its value case that would be given back to workers each year. Under the “Better” pillar, the workforce experience was at the heart of the story. The company highlighted the links between improved worker metrics (employee net promoter scores, worker retention, etc.) and better business outcomes such as customer satisfaction, profit, and innovation.

Beyond these immediate value drivers, a key part of the value case also included metrics around future AI deployment. The experience hub plays a pivotal role in setting the foundation for adoption of more advanced technologies in the company’s future roadmap, bringing value to both workers and the organization.⁴

In another example, Eaton, a global power management company, needed to establish new metrics to measure the value of modernizing its talent acquisition process using AI. Its value case began with metrics that would improve the candidate experience and then expanded to include improved metrics for hiring managers and recruiters. The AI implementation helped the company achieve double-digit increases in these metrics, including time to market, time to present, and time to offer. In addition, the company saw a 30% to 40% increase in candidate velocity and a fourfold increase in its talent network.⁵

Until recently, most technology value cases focused on substitution. The aim of a tech investment was to improve efficiency and productivity, typically by reducing the need for human workers. However, some experts like MIT professor Daron Acemoglu estimate that only 5% of jobs are potential candidates to be replaced by AI in the next 10 years, due to challenges related to reliability and the need for human judgment and oversight.⁶

Many organizations are starting to leverage technology to boost performance through augmentation—for example, by equipping maintenance workers with augmented-reality glasses that show real-time instructions and asset information, enabling them to work more quickly and safely because they don’t have to carry or repeatedly refer to other materials.

Organizations are now moving toward an era of collaboration and convergence between humans and technology.

This movement toward collaboration and convergence puts people at the heart of technology’s value proposition. Organizations can no longer segregate the value of technology from its impact on human beings.

Given people’s central role in capitalizing on next-gen tech, technology that harms human sustainability—for example, by leading to overwork and overwhelm—ultimately stands to undermine its own potential value to the organization.

Conversely, organizations can use technology to pursue a range of potentially valuable human outcomes, including boosting innovation, promoting and supporting collaboration, fostering greater worker well-being, helping workers develop experience, improving job satisfaction, unlocking strategic differentiation for the business, and more. Improvement on those human metrics, in turn, promises to help the organization’s workers—and the organization itself—wring greater value out of its technology.

The convergence of technology and human work has the potential to support human performance and human sustainability to a greater degree than ever before, empowering organizations to make progress on both specific human outcomes and business outcomes beyond productivity and efficiency (figure 5).

Organizations have the potential to create positive feedback loops in which technology investments better cultivate and support their people, who, in turn, create greater value with technology. Start by determining the human performance and human sustainability outcomes you want to achieve, such as workforce happiness and well-being, loyalty, innovation, brand, risk mitigation, and other key outcomes related to talent. As you weigh new human-centered metrics and KPIs for technology investments, ask:

• What human outcomes can technology investments support now?
• In what ways does the introduction of a particular technology change the work being done and alter the human work experience?
• Within the organization, who are the best people to own progress toward this basket of outcomes?

Metrics that include both business and human outcomes can work together in a mutually reinforcing cycle (figure 6), ensuring that as the business grows and succeeds, its workers do, too, leading to a virtuous cycle of continuous improvement.

New approach: Take a cue from research and development with a portfolio approach

Rather than applying the traditional tech investment frame, in which individual investments drive quantifiable efficiencies that produce predictable ROI, consider applying an R&D frame: Assemble a portfolio of investments intended to help your organization advance toward the goals you have identified, with the expectation that the ones that pan out will more than pay for the ones that don’t.

In some cases, the portfolio view may help you rationalize and simplify your organization’s use of technology. You may find that the collection of current and potential technologies threatens to increase the digital busy work your people must cope with and opt to forego investments or undo others.

For example, a company’s desired outcome may be to accelerate the development and launch of new products. It may make several related investments to:

• Make generalized AI tools available to engineers and designers, who will figure out how to apply them to ideation and innovation.
• Deploy new virtual modeling software to help product designers rapidly prototype new product designs.
• Invest in new smart manufacturing tools such as industrial robots and AI-powered quality screening tools to reduce rework and speed time to market.

Any one of these investments may not produce the full desired business outcome in a short time frame, but in combination they could produce transformative results. Continually evaluate the portfolio’s impact on progress toward your outcomes as well as each individual investment’s contribution to it—and be prepared to shift. This ongoing awareness is important for leaders, who may need to make decisions about when to pull the plug and when to make a shift based on a different calculus.

A range of characteristics may indicate whether a more traditional, discrete investment case or a portfolio approach is more appropriate, including the complexity of measuring value, the degree to which realizing the value depends on other conditions, the time horizon for payback, and the uncertainty of the outcomes. Another set of characteristics relates to the diffusion of value across an organization. Is the technology’s impact on a single, clearly defined process or function, or is it spread across multiple areas or the entire enterprise?

New governance: Include interdependencies and multiple stakeholders

Cocreate value cases for new technologies with a broad set of stakeholders across the organization, including workers and leaders in relevant functions. Different perspectives can educate each other: For example, leaders in finance, human resources, or other departments can help IT leaders understand their needs; IT leaders can guide their counterparts toward technology investments that will be most effective for addressing those needs; and workers can provide input on the impact given technologies could have on their lives and work experience.

In some cases, once foundational investments in technology platforms and data are in place, deployment of incremental technologies can move primarily into the hands of business leaders who see novel use cases—this has been borne out at Salesforce, as they’ve rolled out AI-powered agents to support employees.

In another example, Johnson & Johnson’s HR leadership saw an opportunity to break down functional boundaries in creating an HR Decision Science team composed of experts and specialists from across the organization. The cross-functional team is tasked with tapping the organization’s vast data resources to make better end-to-end workforce-related decisions, improve organizational and worker outcomes, and drive science-based and data-driven people decisions across talent practices.¹⁶

One of your key tech stakeholders will likely be your workers, and optimizing the relationship between workers and technology should be a priority. Haphazard accumulation of technology tools, for example, can cause digital workplace overload and anxiety among workers, negatively affecting employees’ psychological well-being.¹⁷ What’s more, evidence suggests organizations are falling short on even the most basic dimensions of employee support for workers as they introduce new tech tools. More than four in five workers (82%) say their organization has not provided training on using gen AI, according to research by Asana and Anthropic,¹⁸ and our 2025 Global Human Capital Trends research indicates that the number-one reason workforce technology investments have failed to meet their investment case is “lack of workforce skills/capabilities.”

Leaders should continuously monitor worker experience with technology, establishing the right metrics for measuring impact, ready to make adjustments as necessary (even if that means pulling the plug on a tech investment).

The value case should encompass not just direct technology costs, but also the ways the organization needs to change for the technologies to help achieve desired outcomes for an increasingly diverse array of stakeholders across functional areas. An ongoing governance and evaluation process should include how the technology is being used. When evaluating and deploying new technologies, embrace user-centric, agile product management practices to implement tech that people actually need, value, and use.

Humans are integral to technology’s promise

Technology is not what it used to be. The shift from automating work to be more efficient to augmenting people’s capabilities to unlock their performance has broad implications for work, and it complicates organizations’ decisions about which tech to purchase, what it can expect to get out of its investments, and how to recognize and measure value.

Organizations that can adapt how they think about and weigh technology investments have the potential to feed a virtuous cycle of human and technological progress, for the mutual benefit of businesses and their people.