Introduction
In an era of rapid technological change—particularly driven by artificial intelligence (AI)—companies are rethinking traditional employment models. One striking example is Standard Chartered, a global bank that has moved toward a gig-style working model for its employees. Through an internal “talent marketplace,” the bank allows many of its staff to take on short-term projects—“gigs”—that may fall outside their formal job descriptions. The aim is to increase flexibility, deploy skills more dynamically, and accelerate AI adoption across the organization.
How the Model Works
Standard Chartered’s model is built around an internal platform (talent marketplace), introduced around 2020. Key features:
Ad-hoc, project-based work
Employees can post or apply for tasks (“gigs”) inside the bank in areas outside their usual roles—for example programming, communications, marketing, or compliance.
Participation during regular work hours
Employees can devote up to about eight hours per week to such gigs, using time during their normal working week rather than separately.
No extra pay for gig tasks
Importantly, these gigs don’t come with extra financial compensation—they’re part of internal development, networking, and skill building rather than additional paid work.
Broad engagement
Approximately 60% of the bank’s global workforce is active on the talent marketplace.
Value generation
The bank claims that this model has delivered over US$8.5 million in value, by enabling projects that might otherwise have been delayed due to hiring lags, or never undertaken.
Skill focus over job descriptions
The philosophy underlying this model is to think of employees not just in terms of their formal job titles, but as collections of skills which can be redeployed as needed. This helps the bank adapt more quickly to technological or regulatory change, especially AI-driven change.
Problems it Seeks to Solve
Several issues are driving Standard Chartered’s shift toward this internal gig paradigm:
- Rigid job roles vs fast-changing demands
Traditional org charts and fixed job descriptions often lag behind new needs—regulatory, technological, ethical that machines or AI tools bring along. The bank wants to be able to reassign skills quickly rather than hire separately for every new demand. - Skill shortages and AI integration
AI deployment requires not only engineers, but domain knowledge (compliance, ethics, etc.), which existing employees may have. Using internal gigs lets the bank leverage those skills more fully. - Retention and employee engagement
Allowing employees to learn new things, collaborate across parts of the bank, and expand their skill set helps reduce attrition, and may increase job satisfaction. The marketplace provides opportunities that might otherwise be outside employees’ direct paths. - Cost and efficiency
By using internal resources rather than hiring externally or setting up new teams for every project, the bank can reduce costs and reduce delays in getting projects underway.
Trade-offs, Challenges & Criticism
While promising, the model also has several trade-offs and potential downsides.
No additional pay for extra work
Because gig tasks are done within standard remuneration, some employees may feel that doing extra or out-of-role work without direct compensation is unfair. There is a question whether “opportunity” or “skill value” compensates for that.
Workload balance and burnout risk
Allowing employees to take on extra tasks may lead to overcommitment—if not carefully managed, employees might feel pressure to take on gigs in addition to their core responsibilities, possibly compromising work-life balance.
Skill mismatch and opportunity inequality
Not all employees may have equal access to gigs—those with more visibility, more confidence, or who are closer to decision makers might benefit more. Some roles may be more “gig-friendly” than others. Also, if gigs are mostly technical or specialised, employees in other roles might not get the same chance.
Potential lack of clarity over roles and accountability
When people work across multiple roles, it can blur lines of responsibility, reporting, and performance evaluation. For instance, whose manager counts the gig-work in performance reviews? How to ensure quality and consistency across ad-hoc work?
Motivation and incentives
Since there is no extra pay, the incentive must come from non-monetary sources: skill building, career advancement, recognition, etc. If those are weak or unclear, participation could diminish, or employees might treat gigs perfunctorily.
Cultural change and resistance
Moving from a model of fixed roles, defined responsibilities, and long-term job descriptions to a flexible skills-based model requires cultural change among managers, HR, and employees. There may be resistance, and misalignment in expectations.
Legal or regulatory concerns
Depending on jurisdictions, how work is classified, labor law obligations, etc., there could be implications. If gigs are substantial in time or responsibility, but considered “internal extras,” there might be disputes about compensation, rights, or benefits.
Implications & Broader Context
Standard Chartered’s experiment reflects larger trends in the workforce and corporate structuring, particularly under the influence of AI. Some implications:
Reimagining employee identity: The notion of jobs being strictly defined becomes less central; instead, skill sets, portfolios of capability, adaptability matter more.
AI and agility: Firms that can move people across tasks may be better placed to integrate AI, because many jobs will evolve (rather than disappear), with new tasks emerging.
Workforce as flexible capacity: Rather than hiring more people for future tasks, firms may prefer to draw on existing headcount more flexibly.
Talent markets internals vs external hiring: Internal gig-markets may reduce dependence on external hiring, especially for niche or emergent skills.
Employee expectations: Those who join the workforce may increasingly expect flexibility, opportunities for cross-functional work, continuous learning.
At the same time, this reflects global gig-work concerns: flexibility vs precarity; skill and opportunity vs inequality; potential benefits vs risk of overwork or undervaluation.
Conclusion
The case of Standard Chartered’s internal gig model offers a compelling look at how a large, traditional financial institution is rethinking the nature of work in response to technological and market pressures. It suggests that a gig-style system within a company can provide many of the flexibility-and-efficiency benefits associated with external gig work—without some of the downsides like precarity or lack of benefits—if designed carefully.
However, to make it successful over the long term, the bank (and any organization considering this model) needs to ensure fairness in opportunity, avoid overburdening employees, maintain clarity of accountability, and ensure that non-financial incentives (skill building, promotion, recognition) are real and meaningful.
For other firms, this experiment provides a prototype: one that may help navigate the future of work. As AI continues to change what we need employees to do, models like internal gig work may become more common—but only if they are balanced with employee welfare, fairness, and clear incentive structures.