SLB launches Tela: AI agents built into its platforms - here's what sales should know
SLB introduced Tela, a new AI tool embedded across its applications and platforms. Users interact through a conversational interface, and Tela agents can work alongside teams or act on their own to interpret well logs, predict drilling issues, and optimize equipment performance.
The company's digital unit is a major growth driver, with revenue up 11% quarter-over-quarter in Q3 and guidance for double-digit year-over-year growth. Leadership says digital will remain central to SLB's strategy for years.
What Tela is (in plain terms)
- Built into SLB's existing software stack - no separate system to sell first.
- Simple chat-style interface for technical tasks that usually need specialists.
- Agents can assist or run autonomously within approved workflows.
- Initial use cases: faster log interpretation, early warning on drilling issues, better equipment uptime.
Learn more about SLB's digital portfolio
Why this matters for sales
- Clear value props: speed, reduced risk, and improved asset performance - easy to link to revenue protection and cost savings.
- Embedded approach: natural attach to existing SLB deployments; lowers cycle time for expansions.
- Multiple entry points: drilling, subsurface, and asset teams - more chances to multi-thread an account.
- Growing budget share: SLB's digital growth signals buyer appetite for AI-enabled workflows.
Sales plays to run now
- Attach and expand: Identify customers already using SLB platforms. Position Tela agents as add-ons to lift usage and outcomes.
- Pilot-led motion: Start with one use case (e.g., log interpretation). Frame a tight 30-60 day pilot with agreed metrics.
- Outcome framing: Sell reduced non-productive time, fewer operational surprises, and faster decisions - not just "AI."
- Multi-threading: Engage drilling managers, subsurface leads, reliability engineers, and IT/data owners early.
- Post-sale expansion: Land one agent, expand to more workflows and teams once KPIs are proven.
KPIs that resonate with buyers
- Time to interpret well logs and deliver recommendations.
- Rate of predicted vs. actual drilling issues caught early.
- Equipment uptime and maintenance intervals.
- Cycle time per well and cost variance.
- Safety-related incidents and unplanned downtime.
Objections you'll hear (and quick responses)
- "Data security?" Clarify where data lives, access controls, and auditability inside existing SLB environments.
- "Black box decisions?" Emphasize human-in-the-loop options, explainability, and clear approval steps.
- "Integration risk?" Point to native embedding within SLB tools and defined handoffs to current workflows.
- "Change fatigue?" Start with one team, one agent, one KPI. Show quick wins before scaling.
What this signals for your pipeline
Budgets are shifting to AI-backed workflows that cut time and uncertainty. Buyers want practical wins they can measure in weeks, not quarters.
Position Tela as a low-friction step inside their current SLB stack. Keep the conversation anchored on operational outcomes, then widen the scope once results land.
Next steps
- Audit current SLB accounts for likely early adopters (drilling ops under cost or timing pressure).
- Propose a scoped pilot with 2-3 KPIs and a clear executive sponsor.
- Prepare a one-page objection brief (security, explainability, integration) to speed up approvals.
Want to sharpen your AI-for-sales approach?
If you're building AI-led sales motions, these resources can help you frame outcomes, pilots, and proof points:
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