Executive summary: a new operating system for work

The future of work is no longer a distant concept; it is a live operating system that business leaders must actively configure. Across industries and regions, four structural shifts stand out:

• Hybrid as the baseline, not the exception. Hybrid and flexible arrangements are now the dominant model for remote-capable roles globally. Fully office-based models are increasingly concentrated in specific sectors, roles, or government segments, even though high-profile return-to-office (RTO) mandates from firms such as Amazon, Dell Technologies and JPMorgan Chase dominate headlines.
• A “hybrid hierarchy” is emerging. When flexibility is unevenly distributed – for example, when senior leaders and scarce specialists work from anywhere while operations staff are required on-site – organizations create a new, powerful hierarchy based on flexibility and location, not just role and level.
• AI is becoming a daily work companion. Tools from Slack, Salesforce, Microsoft, OpenAI and others are shifting from novelty to necessity. Daily AI users are reporting significantly higher productivity, focus and job satisfaction, while also using AI to perform tasks they previously lacked the skills to complete.
• Skills-based hiring is moving from rhetoric to infrastructure. Major employers such as Google, IBM and Delta Air Lines, and more than half of U.S. states, have removed degree requirements from many roles and invested in skills-first approaches. Skills-based hiring is emerging as a structural response to chronic talent shortages and skills mismatches.

For boards and executive teams, the implication is clear: treating hybrid work, AI and skills-based hiring as disconnected initiatives is no longer viable. Leading organizations are instead designing an integrated workforce strategy that aligns:

• where work happens (hybrid design),
• how work is performed (AI augmentation), and
• who gets opportunities (skills-based talent systems).

The following sections outline how this integrated strategy is taking shape – and how business leaders can move from ad hoc experiments to a coherent, future-ready operating model.

Hybrid work and the emerging hierarchy of flexibility

Hybrid is the quiet default behind loud RTO headlines

From a distance, it can seem as though the corporate world is marching back to the office. High-profile RTO mandates from companies like Amazon, Dell Technologies, JPMorgan Chase, Boeing, AT&T and UPS have attracted global attention. Yet behind the headlines, data tells a more nuanced story.

• A recent survey of hybrid and remote employers found that only around 12% of executives plan to implement strict RTO mandates; the vast majority intend to preserve some form of hybrid or flexible work as a permanent feature of their operating model.
• Research from CBRE indicates that, in the Americas, employers now expect an average of about 3.2 days per week in the office, while employees are actually showing up about 2.9 days – a relatively narrow gap that signals a pragmatic equilibrium rather than an all-or-nothing return to 2019 norms.
• A global analysis from McKinsey & Company finds that office attendance remains roughly 30% lower than pre-pandemic levels, suggesting that hybrid work has stabilized rather than reversed.

In short, hybrid is the quiet default. Fully on-site models persist where they are economically or operationally necessary; fully remote models thrive in specific sectors and roles. But for most remote-capable jobs, a structured hybrid pattern – commonly two to three anchor days in the office – is now the norm rather than the exception.

The “hybrid hierarchy”: who gets flexibility – and who does not

While hybrid work is widespread, it is not evenly accessible. A critical dynamic has emerged: a “hybrid hierarchy” in which flexibility becomes another form of organizational power.

In many organizations, senior leaders and highly sought-after specialists are allowed informal “work from anywhere” arrangements. High performers in revenue-critical or AI-intensive roles are quietly given extra latitude on location and hours. Meanwhile, operations teams, junior staff and front-line employees often face tighter badge-swipe requirements and less schedule autonomy.

This stratification is not just anecdotal. Labour market and policy data show:

• In the UK, analysis from the Office for National Statistics (ONS) indicates that around 28% of workers now engage in hybrid work, but access is heavily skewed toward higher-paid, higher-educated professionals. Workers in sectors such as retail, construction and hospitality have far fewer options for remote or hybrid arrangements.
• In the United States, hybrid work remains common across the private sector, but certain public-sector segments are moving in the opposite direction. Following an executive order mandating more in-person work for federal employees, the share of U.S. federal workers in hybrid arrangements fell sharply, while fully in-person roles increased, even as hybrid remains the dominant model nationally.

Within organizations, this dynamic shows up in three ways:

1. Role-based hierarchy. Client-facing, operational and customer service roles are often required to be on-site, while strategy, technology and leadership roles retain greater remote flexibility.
2. Location-based visibility. Those who are physically present more often tend to receive more informal mentoring, stretch assignments and sponsorship – a phenomenon sometimes called “proximity bias.”
3. Performance-linked privileges. Some organizations explicitly tie flexibility to performance ratings, allowing top performers to negotiate more favorable hybrid arrangements than peers in similar roles.

The result is a new, powerful layer added to traditional hierarchies of title, pay and decision rights: who controls their time and place of work. If left unmanaged, this hybrid hierarchy can undermine inclusion and erode trust – especially when it maps onto existing inequities around gender, caregiving status or socioeconomic background.

Implications for real estate, culture and DEI

For corporate real estate and workplace leaders, the hybrid hierarchy is already visible in space utilization patterns. Office occupancy peaks on “anchor days,” often Tuesday to Thursday, with sharp dips on other days. Teams with more bargaining power cluster on favored days and floors, while others are assigned to less desirable time slots or buildings.

For HR, DEI and culture leaders, the implications go deeper:

• Equity risk. If high-flexibility roles are disproportionately held by certain demographic groups – for example, knowledge workers in headquarters locations – while others have limited flexibility, the organization risks entrenching new forms of inequality.
• Leadership modelling. When senior executives insist on office presence for “culture” but are themselves frequently travelling or working remotely, mandates can appear symbolic rather than substantive.
• Engagement and attrition. Research consistently shows that forced, one-size-fits-all RTO policies reduce engagement and increase voluntary turnover, particularly among high-performing and hard-to-replace talent segments.

The takeaway: hybrid is no longer just a scheduling decision. It is a strategic design choice that shapes power, inclusion and performance. Leaders who treat flexibility as a scarce privilege rather than a managed resource risk building a workplace where physical presence, not contribution, becomes the primary signal of commitment.

Fairness, flexibility and the trust gap

What employees actually want from hybrid work

Across regions, employee preferences are remarkably consistent. Surveys of remote-capable workers by organizations such as Gallup show that:

• Roughly six in ten remote-capable employees prefer a hybrid arrangement.
• About one-third prefer to work fully remote.
• Less than one in ten strongly prefer to be fully on-site.

In other words, most employees are not demanding total location independence; they are asking for structured flexibility – a predictable rhythm that blends focused individual work with intentional in-person collaboration.

New workplace behavior patterns such as “microshifting” – designing non-linear days composed of short bursts of focused work interspersed with personal tasks – are also gaining ground. Research from Owl Labs finds that around 65% of workers are interested in this kind of flexible scheduling and are willing to trade a portion of compensation for more autonomy over when they work.

The fairness fault line: mandates vs. mutual flexibility

The deepest tension is not about whether people ever come to the office; it is about how fair and rational the rules feel.

When employees see a clear, role-based logic – for example, customer-facing teams having more on-site time than purely analytical roles – they may not love the policy, but they understand it. When the logic is opaque or feels arbitrary, resistance hardens.

Several consistent patterns emerge:

• Expectation gaps between CEOs and employees. The KPMG 2024 CEO Outlook found that more than 80% of CEOs expect employees to be back in the office full-time within a few years. Employee surveys, by contrast, show strong and persistent preferences for hybrid arrangements rather than a full return. This disconnect fuels what some commentators have dubbed the “Great Office Rebellion.”
• Multigenerational differences. Research from Cisco highlights that flexibility needs vary across generations and life stages. Early-career employees often value in-office time for learning and networking, but they also expect location flexibility to manage cost of living, side projects and caregiving responsibilities.
• Role and income inequalities. As the ONS data in the UK show, higher earners and knowledge workers have much greater access to hybrid work than lower-paid, front-line workers. Without careful design, hybrid models can unintentionally widen inequality.

Employees do not expect perfect equality, but they do expect transparent criteria. When they do not see it, they quickly infer that flexibility is being used as a tool of favoritism or informal power – and trust erodes.

RTO as a retention and employer-brand risk

Fairness perceptions around hybrid work are no longer just an HR issue; they are a strategic risk. Firms that lean heavily on rigid, top-down RTO mandates face three compounding challenges:

1. Higher voluntary turnover. Many talent-market studies now show stronger attrition among employees who feel forced back into the office without a clear business rationale, particularly among high-demand skill segments such as software engineering, cyber security and data science.
2. Reduced engagement and discretionary effort. Employees who feel they are being treated as “children to be supervised” rather than professionals to be trusted report lower engagement scores, weaker alignment to company purpose and lower willingness to recommend their employer.
3. Weakened employer brand. In a global talent market where candidates now routinely ask about flexibility expectations in the first interview, companies with inflexible or opaque policies increasingly find themselves losing out to more adaptive competitors.

By contrast, organizations that ground their hybrid strategy in principles of fairness and transparency see stronger results. Leading practices include:

• Defining work archetypes (e.g., fully on-site, structured hybrid, remote-first) and mapping roles to these archetypes based on business need, not individual preference alone.
• Publishing clear criteria for exceptions and special arrangements, reducing the perception of backroom deals.
• Training managers on outcomes-based management so performance is measured by value delivered, not by visible time at a desk.
• Regularly reviewing hybrid patterns through the lens of DEI, ensuring that access to flexibility does not cluster within specific demographic or status groups.

In the future of work, fairness is not a soft concept – it is a tangible differentiator in attracting, retaining and engaging the talent your strategy depends on.

AI-augmented work: from experiment to everyday indispensable

Daily AI use is exploding

In parallel with the hybrid revolution, work is being reshaped by the rapid integration of artificial intelligence into everyday tasks. What began as isolated pilots in innovation teams has become mainstream behavior.

Recent global research from the Slack Workforce Lab, owned by Salesforce, shows that:

• Over three in five desk workers are now using AI tools in some form at work – a roughly 50% increase in adoption within a matter of months.
• Daily AI use has surged by about 233% in just half a year, marking the fastest-growing workplace technology adoption curve in recent memory.
• Workers who use AI every day report 64% higher productivity, 58% stronger focus and 81% greater job satisfaction than peers who do not use AI.

Complementary research from Salesforce reveals that roughly 96% of workers who use AI have deployed it to complete tasks they previously lacked the skills to perform – from advanced data analysis to drafting technical content and designing presentations.

Meanwhile, a separate survey highlighted by Lifewire found that around 74% of full-time employees are already using AI tools like ChatGPT or Google’s Gemini at work, yet only about one-third have received formal training on how to use them effectively and safely. This training gap is now one of the biggest constraints on realizing AI’s full productivity potential.

From automating drudgery to amplifying human capability

Early use cases for AI in the workplace focused heavily on eliminating “busy work”: summarizing long documents, drafting emails, cleaning data and generating basic code snippets. Those use cases still matter, but the frontier is moving fast toward capability amplification.

Today, leading organizations are seeing employees use AI to:

• Accelerate research and synthesis. Instead of spending hours scanning search results and PDFs, workers use AI to generate structured briefings, identify patterns and surface contradictions in the data.
• Raise the baseline quality of communication. Tools like Microsoft Copilot and other generative AI assistants help employees write clearer proposals, client updates and internal communications, adapting tone and structure to different audiences.
• Prototype creative ideas. Marketing, product and design teams use generative AI to quickly explore campaign concepts, user journeys, interface mockups and even code prototypes, dramatically shortening iteration cycles.
• Support cross-skilling. Employees in non-technical roles use AI to understand concepts in data science, cybersecurity or finance well enough to collaborate more effectively with specialists, reducing translation friction between functions.

The net effect is that AI is increasingly functioning less as a “tool” and more as a cognitive collaborator – one that can dramatically flatten the learning curve into new domains and unleash latent creativity.

The new productivity equation: AI + human judgment

As AI becomes deeply embedded in workflows, the productivity frontier is being redefined. The highest-performing teams are not those that simply automate the most tasks; they are those that:

• Treat AI outputs as first drafts, not final answers, layering in human expertise and context.
• Design workflows where AI handles pattern recognition, draft generation and summarization, while humans focus on framing problems, making decisions and building relationships.
• Continuously refine prompts, instructions and datasets – effectively creating a new organizational capability: prompt engineering at scale.

This has important implications for capability building. In many organizations, AI proficiency is emerging as a new “line three” skill – essential not only for technologists but for managers, analysts, marketers, HR leaders and finance professionals. Over time, the gap between AI-confident and AI-anxious employees is likely to become a primary driver of performance disparities.

Governance, ethics and the AI training gap

AI’s rapid diffusion has outpaced formal training, governance and risk management in most organizations. Common issues include:

• Data privacy and confidentiality. Employees may inadvertently paste sensitive client or internal data into public AI tools, creating compliance and security risks.
• Hallucinations and accuracy. Model hallucinations and subtle inaccuracies can propagate quickly if outputs are not reviewed carefully, particularly among junior staff who may over-trust the technology.
• Bias and fairness. Without strong guardrails and evaluation, AI systems risk amplifying historical biases present in training data – in hiring, lending, content moderation and beyond.
• Shadow AI. When AI use is banned or poorly defined, employees will often use it anyway, without transparency, making risk management harder rather than easier.

Addressing these challenges requires a combination of policy, technology and culture. Leading organizations are moving quickly to:

• Publish clear AI acceptable-use policies supported by examples, FAQ documents and office hours rather than opaque legal text.
• Deploy enterprise-grade AI platforms with built-in privacy, access controls and logging, so employees can safely experiment without exposing sensitive data.
• Launch AI academies and micro-learning programs focused on practical use cases, risks and ethics for different roles and levels.
• Create multidisciplinary AI governance councils that bring together technology, risk, compliance, HR and business leaders to set direction and monitor impact.

The organizations that make AI literacy a core capability – rather than a niche skill – will see the greatest productivity and innovation gains from this new wave of automation and augmentation.

Skills-based hiring as the long-game talent strategy

Why the shift toward skills-first is accelerating

At the same time that work is becoming hybrid and AI-augmented, organizations are rethinking how they identify and deploy talent. Traditional hiring models – anchored in degrees, linear career paths and years-of-experience thresholds – are straining under the weight of structural skills shortages.

Several forces are pushing employers toward a skills-first paradigm:

• Persistent skills mismatches. Many employers report difficulty filling roles, even as millions of capable workers remain underemployed because they lack specific credentials or job titles.
• Rapid job evolution. The half-life of technical skills is shrinking. Jobs in AI, data, cybersecurity and digital operations are evolving faster than traditional education and credentialing systems can keep up.
• Diversity and inclusion goals. Reliance on four-year degree requirements has disproportionately excluded candidates from underrepresented communities, limiting access to economic mobility and reducing the diversity of candidate pools.

As a result, a growing share of employers are formally moving away from “degree-first” filters. Surveys suggest that roughly four out of five employers now claim to have adopted some form of skills-based hiring, up dramatically from just a few years ago.

Major companies – including Google, IBM, Delta Air Lines, Walmart and Bank of America – have removed degree requirements from large portions of their job catalogues, opening pathways for candidates who are “skilled through alternative routes” such as bootcamps, military experience, community college, self-directed learning and industry certifications.

What the data says about outcomes

Early evidence from both private- and public-sector employers suggests that skills-based approaches do more than widen the top of the funnel; they also improve quality of hire and business performance.

Across multiple studies and employer surveys, organizations that have implemented skills-based hiring at scale report that:

• About 90% of companies say focusing on skills rather than degrees leads to better hiring decisions, with fewer mis-hires and lower early attrition.
• Around 94% report that employees hired for skills outperform those selected primarily on the basis of degrees, certifications or years of experience.
• Many employers see higher retention and faster internal mobility among skills-based hires, particularly when paired with structured development pathways and clear internal skills taxonomies.

In the public sector, state governments have become important laboratories for skills-based reforms. In the United States, more than half of states have now issued policy directives to remove unnecessary degree requirements for many public-sector roles, with at least 25 states taking formal action through executive orders or legislation. Early evaluations show a sharp increase in job postings that no longer specify a four-year degree, opening hundreds of thousands of roles to candidates who were previously screened out on paper alone.

The implementation gap: from “skills-washing” to real change

Despite this momentum, there is a substantial gap between aspiration and execution. Research involving millions of job ads and hiring records reveals that:

• While around 81% of employers say they are using skills-based hiring approaches, only roughly a third actually hire more workers without degrees after removing degree requirements from postings.
• Many companies that initially dropped degree requirements for some jobs later reverted to old patterns, particularly when they lacked the internal tools and training to help hiring managers feel confident in skills-based assessments.

This implementation gap – sometimes called “skills-washing” – arises when organizations announce skills-first ambitions but do not invest in the deeper systems required to make them real. Common pitfalls include:

• Superficial job description edits. Removing “BA required” from job ads without redesigning interview and assessment processes leaves hiring managers with the same old mental models.
• Lack of a shared skills language. Without a consistent skills taxonomy embedded in HR systems, managers and recruiters struggle to articulate what skills actually matter for a role.
• Legacy HR technology. Applicant tracking systems and HRIS platforms often remain configured around degrees and years of experience, making it hard to search, screen and promote based on skills.

To move beyond rhetoric, organizations need to treat skills-based hiring as a multi-year transformation, not a communications campaign.

Building a skills-based talent system: practical steps

Leading organizations that have made meaningful progress on skills-based hiring tend to follow a similar playbook:

1. Define a clear skills architecture. Start with a high-level skills framework that covers technical, functional and human skills. Connect this framework to job families, levels and career paths.
2. Redesign critical job roles. Begin with a subset of roles where skills shortages are acute and where degrees are a weak predictor of success. Rewrite job descriptions to focus on outcomes and competencies, not pedigree.
3. Introduce structured skills assessments. Use work samples, job simulations, coding or case exercises and validated assessment tools to evaluate candidates’ capabilities in a fair and consistent way.
4. Reconfigure HR technology. Work with talent technology providers to enable skills-based search, matching and internal mobility in applicant tracking systems and HR platforms.
5. Invest in upskilling and reskilling. Partner with universities, bootcamps, community colleges and online learning providers to create pathways into priority roles for non-traditional candidates.
6. Train managers and recruiters. Equip hiring managers with guidance and training on how to evaluate skills, run structured interviews and avoid over-reliance on proxies such as school names or former employers.

Done well, skills-based hiring is not just a fix for today’s labour shortages; it becomes the backbone of an agile talent system that can rapidly redeploy skills across the business as strategy and technology evolve.

A leadership agenda for the next five years

The future of work is not a single initiative; it is a leadership agenda that spans strategy, technology, talent and culture. Business leaders who want to position their organizations for sustainable advantage in a hybrid, AI-augmented and skills-based world can focus on six priorities.

1. Design hybrid work as a business system, not a perk

• Anchor hybrid decisions in business-critical activities: Which interactions truly benefit from being in person (e.g., onboarding, innovation sprints, client workshops) and which can reliably happen remotely?
• Develop role-based hybrid archetypes with clear expectations for in-office presence, and map roles to them transparently.
• Measure hybrid effectiveness using hard metrics – performance, engagement, time-to-market, retention – rather than relying on anecdotal impressions.

2. Make flexibility fair, visible and principled

• Publish the principles that govern flexibility (e.g., customer first, team-based coordination, role-driven requirements, inclusion safeguards).
• Monitor who gets which kind of flexibility by role, level, gender, ethnicity and caregiving status. Use these insights to address emerging inequities.
• Train leaders to role-model hybrid norms – for example, holding high-quality hybrid meetings, avoiding “office-only” decision making and ensuring remote contributions are heard and recognized.

3. Treat AI proficiency as a core capability for every professional

• Articulate a clear AI vision: how AI will support your strategy, which work will change, and how employees will be supported through the transition.
• Launch tiered AI learning journeys – from foundational literacy for all employees to advanced prompt engineering and product development skills for specialists.
• Embed AI into day-to-day workflows (e.g., CRM systems, collaboration tools, HR platforms) rather than treating it as a separate destination application.

4. Build trustworthy AI governance

• Establish a cross-functional AI council spanning technology, legal, risk, HR and business units to define guardrails and approve high-impact use cases.
• Implement responsible AI principles – fairness, transparency, accountability, privacy by design – and translate them into practical guidelines for product and process owners.
• Regularly audit AI systems for bias, performance drift and security vulnerabilities, and involve affected stakeholders in reviewing outcomes.

5. Build a skills-based talent engine end-to-end

• Develop a skills cloud for your organization: a continuously updated view of current and emerging skills across roles, regions and business units.
• Embed skills into the full talent lifecycle – workforce planning, recruiting, performance management, learning and internal mobility.
• Partner with external ecosystems – universities, community colleges, bootcamps, workforce boards and technology providers – to create skills pathways into and within the organization.

6. Lead with transparency, empathy and ambition

Above all, the future of work calls for a leadership posture that is simultaneously ambitious and human-centered:

• Be transparent about the trade-offs and constraints driving your hybrid, AI and talent decisions.
• Involve employees in co-designing new ways of working, through pilots, listening sessions and structured feedback loops.
• Communicate a compelling narrative of opportunity – how hybrid flexibility, AI augmentation and skills-based mobility can create better careers, not just more efficient organizations.

Organizations that embrace this integrated agenda will not only be better positioned to navigate disruption; they will also be more attractive to the next generation of talent for whom flexibility, technology and growth opportunities are non-negotiable.