Sphera appoints Chris Gutheil as CTO to drive AI-first product execution
Sphera has named Chris Gutheil Chief Technology Officer, putting him in charge of the company's technology strategy and global engineering organization. He joins the Executive Leadership Team, reports to CEO and President Paul Marushka, and is based in Chicago. The move backs a multi-year product roadmap with a stronger push into AI and faster delivery across the portfolio.
Context: software providers are racing to add AI features and rework development practices as customers demand clearer outcomes and shorter time-to-value. Sphera is leaning into that shift-and putting a single executive owner behind it.
AI focus: Sphera AI as the centerpiece
A core part of Gutheil's remit is advancing Sphera AI, which uses operational data to generate insights for teams managing risk and compliance. "Technology-and especially AI-is reshaping how companies operate, manage risk and respond to increasing regulatory and stakeholder expectations," said Paul Marushka, CEO and President of Sphera. "Chris is a proven technology leader who knows how to turn deep data and complex platforms into scalable, high-impact products."
The brief is clear: tighter execution across products, faster releases, and shorter timeframes for customers to see real results after deployments.
Engineering remit: delivery, quality, and integrated AI
Gutheil will strengthen Sphera's global engineering organization and guide development practices, with a focus on integrating AI features directly into products. He'll work across the portfolio and oversee engineering execution end-to-end-from data pipelines and model performance to in-product experiences and rollout.
"Sphera helps companies address some of the most important challenges they face today-operating safely, responsibly, and sustainably," said Chris Gutheil, CTO of Sphera. "I'm excited to leverage Sphera's wealth of data, product technology, innovation, and the capabilities launched through Sphera AI to help customers reduce environmental impact, improve worker safety, and make better, data-driven decisions."
Why this matters for product development teams
- Platform-first AI: Expect shared services (data pipelines, model ops, guardrails) that speed feature reuse across modules and reduce duplicate effort.
- Faster time-to-value: Look for practices like trunk-based development, CI/CD, feature flags, and progressive delivery to compress cycle times.
- Measurable outcomes: More telemetry, outcome metrics, and "time-to-first-insight" targets attached to launches and expansions.
- Governance built-in: Audit trails, data lineage, testing for drift and bias, and clear model change logs-aligned with frameworks like the NIST AI Risk Management Framework.
- Workflow integration: Tighter links to EHS&S, operational risk, and compliance workflows so AI outputs plug into day-to-day decisions-not side dashboards.
- Customer enablement: In-product guidance, documented APIs, and clear upgrade paths so teams can adopt features without heavy services.
Career background
Gutheil previously served as Chief Engineering Officer at QAD, leading enterprise software platform modernization and global engineering at scale. Before QAD, he held senior engineering leadership roles at Accruent. His track record includes large platform transformations and the practical use of AI in both products and development practices.
Company footprint
Sphera provides software, data, and consulting across environment, health, safety and sustainability (EHS&S), process safety, product stewardship, and supply chain risk management. The company reports serving 8,500 customers and more than one million users across 100 countries.
What product teams should watch next
- Release cadence for Sphera AI features and how they're sequenced across the portfolio.
- Time-to-value commitments and post-deployment benchmarks published by product line.
- APIs/SDKs for embedding AI insights into existing customer workflows and tools.
- Model performance reporting, feedback loops, and controls for customer-specific data.
- Security and compliance signals (e.g., SOC 2, ISO 27001) tied to AI services and data flows.
Related resources
Bottom line: Sphera is centralizing ownership of AI execution under a CTO with deep platform experience. For product teams, expect clearer roadmaps, stronger engineering fundamentals, and AI features that connect directly to safety, sustainability, and compliance outcomes.
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