Dr. Mark Bussin’s twelve trends, presented at the South African Reward Association (SARA) conference and summarized in a recent BusinessReport feature, map a clear and urgent agenda for organisations preparing for 2026: AI and analytics will reprice work and leadership, reward models will bifurcate between risk-heavy “moonshot” pay and fairness-driven total‑rewards governance, and cultural shifts driven by younger cohorts will reshape succession, wellbeing and the social contract between employer and employee.
Background / Overview
The SARA conference gathering at the Wanderers Club in Gauteng brought together remuneration specialists, HR leaders and reward practitioners to debate how pay, promotion and total rewards must evolve in the face of rapid technological change. Dr Mark Bussin distilled conference input into a dozen trends that stitch together three recurring themes: (1)
AI and analytics will reprice skills and job structures, (2)
leadership and culture are shifting toward motivational, non‑coercive models, and (3)
total‑rewards design must reconcile ambition (moonshot incentives) with accountability and fairness.
Many of the trends are already visible in market activity: enterprise copilots and multi‑platform AI adoption are reshaping daily workflows, public trackers show large numbers of AI‑cited layoffs in 2025, and compensation committees face heightened scrutiny after high‑profile executive awards. These contextual facts underpin Bussin’s list and inform the practical checklist HR and reward teams must adopt now.
The 12 trends — summary and practical implications
1) More entrepreneurs: AI lowers barriers to entry
Bussin argues that inexpensive AI building blocks, low‑code platforms and off‑the‑shelf models will accelerate niche startup creation and entrepreneurial exits from large employers. Organisations should expect increased competition for specialist talent and for domain experts who can pair subject matter knowledge with AI tooling.
What to do now:
- Create internal incubators, equity pathways or “startup sabbaticals” to channel entrepreneurial energy inward.
- Introduce rotational, product‑owner roles that mimic startup autonomy to retain high‑agility employees.
2) Moonshot pay: outsized, milestone‑contingent compensation
Expect more organisations to design
moonshot compensation: large, milestone‑contingent packages aimed at audacious targets. These packages can attract visionary leaders but pose governance, optics and fairness risks—particularly when awards scale into headline‑grabbing figures. Boards must treat moonshot awards as high‑risk governance events requiring independent fairness reviews, staged milestones, clawbacks and transparent reporting.
Risks to flag:
- Reputational fallout from perceived inequality or misaligned large awards.
- Legal and shareholder challenges where processes or disclosures are insufficient.
3) Promotions belong to data slicers: the data skill premium
The ability to extract, interpret and translate insight from large datasets—what Bussin calls
data slicing—will be a primary currency for promotion. Roles such as MLOps leads, prompt engineers, model auditors and AI‑orchestration specialists are in short supply and command premium rewards. HR promotion rubrics must be updated to recognise AI supervision and data orchestration as promotable competencies.
Practical changes:
- Add AI fluency and demonstrable data‑orchestration tasks to promotion criteria.
- Fund micro‑credentials and enterprise sandboxes for on‑the‑job skill validation.
4) Digital detox: reward systems will protect off‑hours
A countertrend to “always‑on” work is emerging: employees increasingly demand
digital detox outside work. Organisations that operationalise boundaries—right‑to‑disconnect policies, enforced email windows and explicit stipends for wellness—will see retention and mental‑health benefits. Evidence from enterprise surveys and practitioner reports supports the ROI of structured digital‑wellness programs.
Suggested features:
- Policy‑level no‑email windows and paid offline focus days.
- Measured pilot programs to track the effect on attrition and productivity.
5) The iceberg of ignorance melts: analytics reduce leadership blind spots
Better people analytics will reduce the classic “iceberg of ignorance” by surfacing root causes behind attrition and performance gaps. But data alone is insufficient: organisations must pair analytics with remediation pathways and safeguards against biased or misleading signals. Expect leaders to demand explainability and human‑in‑the‑loop checks for any AI‑driven HR action.
Operational recommendations:
- Publish anonymised dashboards for promotion and attrition drivers and require remediation plans when leading indicators diverge.
- Mandate explainability assessments for HR models and maintain audit logs.
6) No toxic leaders: culture and accountability rise
There is rising intolerance for toxic leadership. Smaller firms are following multinational examples by removing coercive managers and tying executive pay and promotion to validated culture and retention KPIs. Compensation committees should link portions of executive pay to psychological‑safety metrics and validated cultural outcomes.
Implementation steps:
- Integrate culture metrics into C‑suite KPIs and reward plans.
- Use independent culture audits as part of executive appraisal.
7) Unemployment ravages the globe: AI‑linked downsizing and uneven effects
Bussin warns that corporate downsizing to fund AI investment will increase unemployment in affected functions—particularly routine, entry‑level and middle‑management roles. Public trackers and industry reporting cited tens of thousands of 2025 job cuts that explicitly referenced AI as a proximate cause; these are signal‑level data rather than causal proof, but they are material for scenario planning.
Mitigation strategies:
- Prioritise redeployment and funded reskilling before layoffs.
- Publish placement and retraining outcomes when workforce reductions occur.
8) Conscious unbossing: new leadership appetites
Gen Z and Millennials increasingly favour autonomy, coaching and self‑managed career paths over traditional hierarchical advancement. Organisations that force line‑management as the only path to senior roles risk succession gaps. The remedy is a lattice career architecture that recognises expertise, influence and cross‑functional leadership outside the line.
Action points:
- Create dual career tracks (technical and managerial) with equitable reward parity.
- Invest in mentorship and rotational experiences to cultivate leadership without forcing promotion into line management.
9) Radical changes in education and parenting: societal shifts affect the workplace
AI’s diffusion will reshape schooling and parenting norms, producing graduates with micro‑credentials, practical AI sandboxes and different communication styles. Employers should partner with education providers to codify stackable credentials and apprenticeship pathways that reflect workplace realities.
Long‑term employer play:
- Sponsor accredited micro‑credentials and enterprise sandbox access for universities and technical schools.
- Build apprenticeship pipelines with measurable placement targets.
10) C‑suite clarity: AI and analytics reshape leadership
AI and analytics will demand clearer cross‑functional leadership, with data fluency becoming a boardroom expectation. Organisations treating AI only as an engineering problem—not a strategic capability—risk misalignment and poor governance. Embed a senior AI governance sponsor on the executive team and formalise decision rights for high‑stakes model deployment.
Governance checklist:
- Assign a C‑level sponsor for AI governance.
- Require risk‑adjusted business cases and post‑deployment monitoring for major models.
11) You must know ChatCoGem: multi‑platform AI literacy
Bussin’s shorthand
ChatCoGem—referring to ChatGPT, Microsoft Copilot and Google Gemini—captures a pragmatic truth: employees who know how to orchestrate multiple AI platforms will have a distinct edge. Enterprises will prefer candidates who can manage multi‑vendor toolchains and avoid single‑vendor lock‑in. This is supported by vendor integrations of copilots into core productivity suites and by practitioner recommendations for tenant‑grounded training.
Talent interventions:
- Provide hands‑on training across major copilots and create evaluation criteria for “AI orchestration” in job descriptions.
- Maintain enterprise sandboxes and tenant‑grounded instances for safe practice.
12) The world’s first trillionaire: extreme wealth and compensation debates
Finally, Bussin raises a provocative scenario: the arrival of unprecedented private wealth (a hypothetical “first trillionaire”) would intensify debates over executive compensation, public policy and corporate governance. While the creation of such an individual is speculative, the underlying point is practical: escalating extremes of wealth and headline executive awards will force boards to prepare robust legal justifications and shareholder engagement plans.
Board‑level preparations:
- Model public reaction scenarios and pre‑define disclosure narratives.
- Strengthen fairness and fiduciary documentation for any outsized awards.
Cross‑cutting strengths, risks and governance imperatives
Why organisations that act early will win
- Strategic total‑rewards design becomes a competitive advantage: aligning pay philosophy, promotion criteria and wellbeing policy reduces churn and amplifies performance.
- AI fluency and governance unlock productivity while containing risk. Organisations investing in MLOps, model observability and human‑in‑the‑loop processes can scale safely.
- Culture and leadership reform—removing toxic leaders and rewarding motivational behaviours—improves retention and employer brand.
Key systemic risks
- Vendor opacity and contractual gaps: Overreliance on proprietary model claims without contractual audit rights creates hidden liabilities. Organisations must demand testable SLAs and third‑party verification rights from AI vendors.
- Rapid cuts without redeployment: Funding AI capacity by indiscriminate cuts can hollow entry‑level pathways and cause long‑term talent scarring. Public trackers show AI frequently cited in 2025 layoffs; use these figures as scenario signals, not deterministic forecasts.
- Governance failures for moonshot pay: Astronomical awards invite regulatory, shareholder and public scrutiny; boards must document process, fairness reviews and clawback mechanisms to withstand challenge.
Verifying the load‑bearing claims — what’s confirmed and what’s speculative
Several claims in Bussin’s list are well‑supported by market signals and practitioner reports; others remain scenario‑based and should be treated with caution.
Confirmed signals:
- Widespread vendor integration of copilots (Copilot, Gemini, ChatGPT) into productivity suites is observable in vendor roadmaps and enterprise rollouts, supporting the ChatCoGem imperative.
- Large numbers of AI‑attributed layoffs in 2025 were tracked by public instruments and reporting; while attribution differs by methodology, the numbers are material enough to inform risk planning.
- Market premium for data and AI‑orchestration skills is documented in labour‑market activity and corporate hiring priorities, validating the “promotions belong to data slicers” claim.
Speculative or unverifiable claims (flagged):
- The world’s first trillionaire is a plausible thought experiment but remains speculative; any specific regulatory or compensation outcomes tied to such an event are hypothetical until concrete wealth events occur. Treat this as a scenario, not a forecast.
- Exact magnitude and timing of job losses due to AI cannot be precisely predicted from public trackers alone; different trackers use different methodologies and count only explicit attributions. Use the trackers for scenario planning rather than deterministic forecasts.
- Claims of guaranteed productivity ROI from AI deployments should be treated cautiously unless tied to independent measurement and pre‑specified KPIs; vendor PR alone is insufficient.
Practical, high‑impact checklist for HR, reward committees and IT leaders
- Reframe total rewards as a strategic capability: publish a total‑rewards playbook linking pay philosophy, promotion criteria, culture metrics and wellbeing policies, and secure CEO and board sign‑off.
- Embed AI governance into reward decisions: require explainability, human validation, exportable logs, and contractual audit rights from AI vendors.
- Build reskilling and mobility programs: fund apprenticeships, micro‑credentials tied to promotion, and enterprise sandboxes. Track placement outcomes at 6/12/24 months.
- Protect work‑life boundaries: introduce enforceable “no email” windows, paid offline days and digital‑wellness stipends; measure uptake and retention impact.
- Redesign leadership development for unbossing: create lateral career tracks, coaching focused on motivational competencies, and include psychological safety metrics in executive scorecards.
- Run independent compensation fairness audits following AI‑driven workforce changes; remediate disparate impacts publicly and promptly.
For Windows‑centric IT leaders and enterprise architects
- Plan for Copilot‑style features embedded across Windows and Microsoft 365: expect changes to endpoint telemetry, patch cadence and data‑protection policies. Negotiate vendor transparency on model training, access logs and data residency.
- Prioritise observability for AI: implement MLOps and model observability tools that capture provenance, decision lineage and drift metrics; budget human‑in‑the‑loop checks on high‑risk outputs.
- Avoid single‑vendor lock‑in where possible: design multi‑vendor sandboxes and cross‑platform competency programs (ChatCoGem) to retain bargaining power and governance flexibility.
Final analysis — strengths, trade‑offs and what to watch in 2026
Dr Bussin’s twelve trends offer a coherent, action‑oriented framework that marries strategic reward design to the practical realities of a fast‑moving AI economy. The strengths of the framework lie in its synthesis: it links talent strategy, governance, culture and compensation into a single operating narrative that HR and boards can execute against. Organisations that treat total rewards as a strategic capability and invest in AI fluency, governance and humane culture practices will be well‑positioned to attract and retain top talent.
Yet the trade‑offs are real. Moonshot pay can generate headline value but also invites legal and reputational risk if governance is weak. Rapidly funding AI by cutting jobs without credible reskilling will create long‑term talent deficits and regional economic damage. Vendor opacity remains a persistent governance hole that procurement and legal teams must seal with contractual audit rights and SLAs.
What to watch in early 2026:
- Regulatory and shareholder responses to large executive awards and AI‑driven workforce reductions.
- Evidence of cross‑vendor AI orchestration capability becoming a formal job requirement in role descriptions.
- Public reporting (placement rates, retraining outcomes) from large employers following AI‑linked reductions; these will be the clearest signals of corporate responsibility in practice.
Conclusion
The twelve trends outlined at SARA are more than prognostication; they are a practical playbook for the near term. Organisations that integrate AI governance, update promotion and reward rubrics for data fluency, protect employee wellbeing through concrete digital‑detox policies, and design moonshot incentives with rigorous governance will navigate 2026 with advantage. Conversely, those that treat AI merely as a cost lever or ignore culture and governance will create avoidable risk across reputation, regulatory exposure and talent pipelines. The work for HR, rewards committees and IT leaders is urgent but actionable: a coherent total‑rewards strategy, backed by AI observability and transparent governance, is the single best lever to secure performance and trust in the next phase of the workforce transformation.
Source: businessreport.co.za
12 employment and remuneration trends to watch for in 2026