Goldman Sachs plans AI-led job cuts under “OneGS 3.0,” signaling a shift in finance. Learn what roles are at risk and how professionals can adapt.
You open your mail or internal Slack: “Expect more rounds of job cuts.” In 2025, even veteran bankers are waking up to texts like these. Goldman Sachs’ recent internal memo warns employees of further AI-led job cuts under its new OneGS 3.0 strategy.
The phrase “AI takeover” has become less sci-fi and more workplace reality — and Goldman is among the high-profile firms placing the bet.
In this post, we dive deep into that memo, unearth the structural shifts behind it, explore what it means for employees, and equip you — whether in banking, tech, or a support function — to navigate, adapt, and find agency in turbulent times.
What’s in the Memo? Dissecting Goldman Sachs’ Announcement
To understand what’s happening, we must first decode the internal communication.
Key Messages & Strategic Framing
- The memo, apparently signed by CEO David Solomon, President John Waldron, and CFO Denis Coleman, introduces OneGS 3.0, a transformation initiative built around AI, efficiency, and structural reorganization.
- It states Goldman will implement a “limited reduction in roles across the firm” and constrain headcount growth through year-end.
- The memo emphasizes that AI-related gains should be reinvested into client services — the narrative is not “firing for cuts,” but “reshaping for growth.”
- It also places selected priority workstreams — sales enablement, client onboarding, lending, regulatory reporting, and vendor management — as early targets for AI reengineering.
- Interestingly, even with the cuts, Goldman expects a net increase in overall headcount by year-end — implying that some divisions will still hire, while others shrink.
In short: the move is not an indiscriminate purge, but a calibrated rebalancing in service of AI-driven efficiency.
What Has Changed vs. Past Cuts
Goldman has conducted regular workforce reviews in past years. In early 2025, it reportedly considered cutting 3%–5% of staff as part of its performance evaluation process.
What’s new now:
- AI as the catalyst: The cuts are explicitly couched in terms of AI transformation, not just cost control.
- Headcount growth cap: Unlike prior cuts, this one also includes a hiring freeze or severe moderation across many functions.
- Structural rewiring: Emphasis on reworking internal processes (“front-to-back workstreams”) rather than only cutting layers.
Key takeaway: This is not a reactive retrenchment — it’s a proactive transformation. Goldman is signaling that AI is not auxiliary; it’s becoming the operating backbone.
Why Now? Forces Driving AI-Based Restructuring in Finance
This memo did not emerge out of thin air. It arises from intersecting pressures and opportunities.
Margin Pressure & Cost Inflation
Finance is labor-intensive. Technological tools, regulatory burdens, compliance, and talent costs all squeeze margins. Goldman’s 2025 compensation costs have already swelled, prompting pay scrutiny.
When revenue growth is uncertain, organizations look to productivity levers — and AI is currently the strongest lever available.
AI’s Rapid Maturation (From Assist to Autonomy)
Years ago, “AI in finance” was largely predictive analytics or risk modeling. Today, generative AI, copilot applications, internal assistants (Goldman’s own “GS AI Assistant”), and workflow automation are maturing quickly.
Hence, roles previously thought safe — report drafting, compliance checks, internal operations — can now be rethought.
Client Expectations & Speed Imperative
Clients increasingly expect real-time insights, faster onboarding, seamless interaction. AI can shave latency and deliver scale. Firms that adapt faster gain competitive edges. Goldman’s memo emphasizes speed, agility, and client experience.
The “Efficiencies to Reinvest” Messaging
A smart narrative: instead of just cutting, the firm says it will reinvest AI savings into client-facing areas. This ensures the transformation is seen not as shrinkage, but reallocation toward growth functions.
Key takeaway: The layoff signals are not just cost control — they’re turning points in how financial firms embed AI in their DNA.
Which Roles Are at Risk — and Which May Survive?
Understanding which job types are vulnerable — and which could be repositioned — gives professionals critical foresight.
High-Risk Functions
- Routine / Process Roles: Roles involving standard workflows, data entry, compliance checks, or reporting that could be automated.
- Middle-Back Office: Operations, vendor contracts, reconciliation, regulatory reporting — all classic targets for AI lifts.
- Entry-Level Analysts / Assistants: Tasks often focused on summarizing, formatting, doing manual research.
- Support Functions with Low Differentiation: Teams in procurement, internal admin, or redundant chain linkages.
Roles With Comparative Immunity (for Now)
- Strategic, Judgment-Heavy Roles: Deal structuring, M&A advisory, high-stakes negotiation, leadership, client interaction.
- AI Oversight, Ethics, Governance: As AI grows, humans are still needed to monitor, audit, explain, and guide usage.
- Creative & Human-Centric Functions: Roles involving storytelling, relationship-building, vision-setting, culture-building.
- Cross-Functional Integrators: Professionals who can bridge AI tools + business context + people — in short, translators.
Possible Repositioning Opportunities
For those in roles under pressure, a path may remain:
- Reskilling to AI / automation roles within the firm
- Becoming internal consultants who guide AI adoption in units
- Shifting to roles in oversight, audit, risk, where domain background matters
- Transitioning to project-based or hybrid roles combining tech + domain
Key takeaway: No career is entirely safe — but roles anchored in judgment, oversight, integration, and originality are more resilient.
What Professionals Can Do — Action Steps
Whether you’re in banking, finance, technology, or adjacent fields, the shifts at Goldman hold lessons. Here’s a blueprint for proactivity.
1. Accept the Change — but Don’t Capitulate
The first step is emotional: resistance, denial, or panic are natural. But the most dangerous posture is paralysis. Treat this moment as a signal, not a sentence.
2. Audit Your Role with an AI Lens
Walk through your job duties one by one:
- Which tasks are rote, predictable, or rule-based?
- Which involve discretion, judgment, creative adaptation, people nuance?
- Which parts could AI or automation handle within 1–3 years?
Map out which parts of your job are “at risk,” and which are core to your value.
3. Acquire AI Literacy & Tool Fluency
- Learn how generative AI, prompt engineering, and automation pipelines work.
- Experiment with tools (ChatGPT, Copilot, domain-specific assistants).
- Understand the constraints, biases, risks of these tools.
- Even if your role is non-technical, being conversant is an edge.
4. Build a “T-Shape” Profile
- Deep specialization in your domain (e.g., finance, compliance, underwriting)
- Broad adjacency skills: data analytics, automation, system thinking, change management
- This gives you flexibility to shift horizontally or vertically when necessary.
5. Quantify & Document Your Contributions
Especially in uncertain times, your track record is your resume:
- Maintain a portfolio of projects, outcomes, metrics
- Write internal “playbooks,” process docs, knowledge repositories
- Be visible in cross-functional initiatives, AI pilots, transformation efforts
These artifacts help anchor your value.
6. Network Proactively
- Within your firm: find AI transformation teams, innovation groups, cross-department bridges
- Outside: join domain & AI communities, LinkedIn groups, peer circles
- Have mentors who understand both domain and future of work
When restructuring hits, internal movement becomes possible faster than external seeking.
7. Financial & Career Safety Nets
- Build a savings buffer (6–12 months)
- Keep your resume updated, portfolio live
- Explore side projects, freelance gigs, consulting in domain or tech crossover
- Monitor talent demand shifting trends — stay ahead of curve
8. Cultivate a Growth Mindset & Emotional Resilience
Change is emotionally draining: fear, uncertainty, identity crisis. Practices help:
- Mindfulness, journaling, coaching
- Peer groups or accountability partners
- Focus on what’s in your control — learning, connections, small wins
Key takeaway: The professionals who will thrive are not those who avoid change — but those who lean in, learn fast, and reinvent themselves with intent.
Why Some Companies (Like Goldman) Embrace the Pain
We’ve discussed individual strategies. Let’s also examine the rationale from the firm perspective.
Strategic, Not Merely Tactical Cuts
Goldman frames this move not as a cost measure, but as strategic repositioning. They view AI as a lever to reshape the entire operating system, not simply replace headcount.
By investing cuts in working functions and reallocating capital into growth or client-facing units, the firm is attempting to optimize its organizational architecture for a new era.
Guarding Against Disruption
In finance, competitive advantage often lies in latency, speed, integration. Firms unable to modernize risk being disrupted by more nimble, AI-native players. Goldman’s move, then, is partly defensive.
Signaling & Culture Reset
Large firms often use bold transformation to reset internal culture: pushing urgency, flattening silos, and reorienting how work gets done. OneGS 3.0 is a message that legacy modes are evolving.
Talent Reallocation Over Mass Cuts
The expectation of net headcount growth (overall) indicates Goldman is not starved for talent — it wants the right talent in the right seats, aligned with AI-first workflows. Some legacy roles may be phased out, but new roles may form. Reuters+1
Key takeaway: This is not purely cost-trimming — it’s an organizational bet that AI will shift which roles matter, where capital flows, and how value is created.
Warnings, Misconceptions & Things to Watch
Even as we dissect the memo and implications, we must highlight what not to overread.
Misconception: “AI Will Replace Everyone, Immediately”
The transformation is incremental. Many roles will be augmented, not eliminated. Human judgment, ethics, oversight, relationships still matter deeply.
Signal vs. Noise — Not Every Role Is Doomed
The memo speaks of “limited reductions” and constraints — not wholesale culls. Because AI implementation takes testing, iteration, oversight, not mass rollout.
Watch the Execution, Not Just the Promise
Firms often promise AI transformation, only to lag in execution. The real test is how fast pilots scale, how governance evolves, how culture adopts change.
Be Alert to Bias, Misuse, Ethical Risk
As AI takes over more work, it may embed hidden biases, reduce oversight, amplify errors. Roles in audit, governance, ethics might expand in importance.
Secondary Effects & Ecosystem Ripples
- Vendors, service partners, compliance firms, back-office outsourcers may feel shocks
- Geographical shifts: offices in lower-cost regions may absorb more work
- Regulatory scrutiny may increase — financial regulators often have low tolerance for black-box decisions
Final Thoughts & Reflection
Goldman Sachs’ memo isn’t just a banking story — it’s a canary in the coal mine for all industries. When a storied, status-quo giant pivots so overtly around AI, the signal is loud: the future of work is being redrawn, and no function is sacred.
If you are in a domain where routine meets decision, where operations meet judgment, where systems and people intersect — your moment of agency is now. The path forward is not to outrun the change, but to ride its shockwaves.
Ask yourself: Which part of my work is already replicable? Which part is uniquely mine? How can I amplify the latter?
I’d love to know your thoughts: do you feel your role is vulnerable? Are you already learning AI tools? Comment below — let’s talk concretely about how to prepare, not panic.
