Countering disruptions with dynamic total rewards strategies: Actions for 2026

Challenge

WTW's most recent Global Medical Trends Survey shows healthcare costs are expected to increase at double digit rates in 2026 as more care options emerge, employer-provided coverage expands, and unit costs increase. This is particularly acute in the U.S., where the frequency and severity of high-cost claims have increased significantly over the past 10 years and pharmacy costs now represent 40% of overall healthcare spend.

These costs are unsustainable and squeeze total compensation spend. For employers, the traditional approach of shifting costs to employees — raising premiums or reducing coverage — has reached its limit.

Action

Break the pattern of annual "tweaks" and embrace disruptive solutions. For example:

• Implement alternative plan designs with sophisticated navigation and decision support to steer employees to higher quality, more cost-efficient care (e.g., narrow networks, variable co-pay arrangements, third-party centers of excellence)
• Achieve better precision with budgeting and identify cost optimization opportunities by combining with AI-enabled predictive analytics to get in front of potential high-cost claims (e.g., cell and gene therapies)
• Implement direct contracting or direct access solutions to obtain the lowest cost for targeted treatment areas (e.g., for GLP-1 weight loss drugs)
• Shed undervalued or under-utilized programs (regardless of prevalence in the market), as complexity can add cost while simplicity can drive value and appreciation
• Enhance processes for monitoring fraud, waste and abuse
• Implement choice programs where employees can direct fixed employer subsidies to benefits programs that are most impactful to them
• Leverage employer benefits captives for access to data and insights to understand claims drivers and support population health

Outcome

Flattening the trajectory of healthcare cost increases will free up funds to invest in other areas of rewards, including acquiring necessary critical roles and skills to support broader business transformation and automation ambitions.

Challenge

There continues to be an acute shortage of critical skills, especially in light of developments related to AI and its supporting infrastructure. The "buy" strategy — hiring externally — is becoming prohibitively expensive and disruptive to internal equity, while the "build" strategy — training internal talent — is often too slow to meet immediate needs.

According to WTW's 2025 Skills Survey, a majority of organizations see the importance of skills, but only 30% have any form of foundational infrastructure such as a skills taxonomy or tracking process. Moreover, there is often no consistency in skills proficiency and how skills tie to work and job requirements. Inertia tends to take root in the perception that building a skills infrastructure is too significant of an undertaking to take on despite its clear value to the business.

Action

Bridge the gap between the demand (i.e. business needs) and supply (i.e., recruiting, talent development) of skills. Tactical applications include:

• Define the primary use cases for skills for your organization, such as to enhance recruiting, learning and development, and/or pay practices
• Implement digital platforms to help employees more effectively learn about new skills that are important to the organization, build new skills and visualize and navigate career opportunities
• Utilize consistent pay policies and programs to reward employees for acquiring critical skills, rather than relying on ad-hoc sign-on bonuses or unregulated pay premiums
• Proactively manage internal equity concerns by articulating skills as a factor of pay and career decisions, and ensure that that there is equitable access to acquiring skills
• Support learning with sabbaticals for study and tuition assistance focused on future skills

Outcome

A thoughtful career and skills strategy can help organizations be more effective in acquiring and retaining critical talent to unlock significant productivity, which will be a key differentiator in a highly competitive market.

Challenge

Advancements in AI and data sciences create exciting opportunities for total rewards teams to make more informed decisions and support better member experiences. However, AI cannot be effectively leveraged without a strong foundation (e.g., proper data readiness and governance, user skills and knowledge, and robust vendor evaluation processes).

Action

AI-enabled technology is a means, not a destination. Successful AI adoption within total rewards starts with getting the data right, building skills within the team, and focusing your attention to the areas with the greatest return on investment. Specifically:

• Ensure human-in-the-loop processes to minimize bias and improve accuracy of outputs (e.g., use diverse data sets to train AI, audit and review AI-generated content, and establish a robust data governance framework to keep data updated)
• Organize data to be AI-ready, by understanding what data you have, what data you need, and how to build accessible data sets (e.g., data from unstructured policy and plan documents that can be extracted into structured data sets, reviewing data sources and content for opportunities to cross-reference analytics and insights)
• Link internal and external data to provide and visualize richer insights for decision making (e.g., exit interview findings linked with web-scraped talent movements and sentiment analysis to inform benchmarking peer group selection)
• Use additional market intelligence, enabled by AI, to supplement traditional data sources and make informed rewards decisions (e.g., even with its limitations, real-time pay data can provide supplemental insights not captured in traditional compensation surveys)
• Prioritize potential AI-enabled point solutions with the greatest value-add (rather than getting fatigued by endless demos)
• Break down workflow across total rewards areas and assess what can be enhanced by generative and agentic AI (e.g., automated job evaluation, analytics in benefits utilization, data error detection, updating policy documents) to improve process efficiency
• Evaluate the quality and security of data infrastructure

Outcome

Getting the foundation right allows organizations to amplify the impact of pay and benefits strategies with AI, improve operational efficiency within the total rewards team, and achieve more informed decision making of the rewards spend.

Challenge

Against the backdrop of cost constraints, reduced volume in talent movement across employers, and employee burnout and financial stress, ensuring employees understand and appreciate their rewards and are equipped to navigate life events is more important than ever.

Passive forms of communication — where employees must actively seek out information related to pay, career and benefits — is no longer sufficient. Employees assume organizations know who they are and what they need, and they expect hyper-personalized, predictive support.

Action

Leverage the power of AI to move from reactive to predictive models of employee engagement. Examples include:

• Use digital platforms and tools to personalize pay and benefits information, anticipate individual employee needs, provide nudges that drive behavioral change (e.g., saving for retirement, making healthier lifestyle choices), help employees optimize reward elections, and promote career development paths and learning and development opportunities aligned with individual growth aspirations and business needs
• Leverage agentic AI functionality — accessing information and resources across vendor platforms — to provide employees next-step support in key moments of engagement
• Apply deep learning in the evaluation of population health and financial wellbeing, creating personalized remediation plans and high-touch educational opportunities (e.g., recommendations on coverage and allocation of contributions across tax-efficient spending and saving accounts)
• Listen and pulse to create meaningful two-way engagement with employees to understand evolving employee needs and values

Outcome

Predictive and personalized employee engagement solutions can increase employee appreciation and understanding of the total rewards offerings, improve workforce health, wellbeing, and productivity, and provide a greater return on the overall rewards investment.

Challenge

Regulatory uncertainty, such as delays in local transpositions of the Directive, may tempt organizations to wait for clarity rather than taking charge. Organizations may also be inclined to relegate pay transparency to local total rewards teams given the complexity of potential legislative differences across EU countries. A disjointed approach – without clear protocols for computations (e.g., dry-run calculations) and communications – may erode trust and could hurt the employer brand.

Action

Forge ahead on the pay transparency journey, considering the following actions:

• Use consistent principles, regardless of differences in locally transposed requirements, to build a scalable transparency framework that can be adapted across different markets and regulatory environments, even for jurisdictions where requirements are less stringent
• Thoughtfully plan communications with leaders, managers, employees and their representatives, demonstrating authentic support for transparency
• Document deficiencies in data infrastructure and develop a clear roadmap to address gaps, including proper budgeting for potential remediation plans
• Proceed with "dry run" calculations and have a clear process in place to address employees' requests for information (including how pay and benefits values will be collated and calculated, as well as the form and means of communication) despite local legislative delays

Outcome

Proactiveness towards transparency requirements will help organizations leapfrog those who scramble to comply with ever-changing regulatory requirements, turning a compliance exercise into an opportunity to build employee trust and loyalty and properly budget for remediations.