Sphere Newsletter — May 2026

We’re back with a new edition, and there’s plenty to catch up on.

This month, we’re looking at where AI investment is turning into real business value, how companies are assessing their readiness, and which emerging technologies are moving from concept to practical application.

Let’s start with what the market is talking about.

AI ROI Starts with AI Readiness

Many companies are investing heavily in AI, but only a smaller group is turning that activity into measurable business value. PwC’s latest AI performance study found that the most “AI fit” companies generate AI-driven revenue and efficiency gains that are 7.2x higher than others.

The takeaway is clear: AI ROI does not come from launching more pilots. It comes from building the right foundation, aligning AI with business priorities, and applying it where it can drive growth, reinvention, and measurable performance improvement.

For organizations evaluating where they stand today, AI maturity is becoming a practical business question, not just a technology question.

Read the PwC article on AI ROI → (opens in new tab)

AI Spend Is Rising. Control Is the Next Priority

Enterprise LLM usage is growing fast, but so is the challenge of managing cost. Many organizations are shifting toward infrastructure-based models to reduce unpredictable API spend and gain long-term efficiency.

Read the report on Kong HQ → (opens in new tab)

Why Data Control Is Driving Private AI Adoption

As AI becomes embedded in daily workflows, companies are prioritizing environments where sensitive data stays internal. Private deployments give teams the ability to leverage AI without exposing proprietary information.

See what McKinsey thinks → (opens in new tab)

Open-Source AI Is Changing the Equation

Open models are making private LLMs more accessible than ever. Organizations are increasingly combining open source flexibility with enterprise-grade controls to build AI systems for their own terms.

Learn more from the Linux Foundation → (opens in new tab)

Sphere Announces Govarix: The Secure Bridge Between AI Innovation and Global Regulation

Govarix is a next-generation enterprise AI platform specifically engineered for companies operating within highly regulated markets. Launching in May 2026, the platform bridges the gap between accelerating AI adoption and tightening global regulations, such as the EU AI Act and NIST AI RMF. Unlike standard cloud-only AI tools, Govarix is a self-hosted solution, ensuring that sensitive data never leaves your internal infrastructure.

The platform features a comprehensive suite of modules designed to meet modern operational and regulatory demands. This includes a self-hosted RAG knowledge platform, an AI Act compliance wizard, and industry-first CSRD carbon reporting to track AI-related emissions. With a built-in security layer featuring prompt injection guards and immutable audit logs, Govarix provides a secure, auditable path for sectors like healthcare, financial services, and legal to deploy AI with confidence.

We have a proven track record of helping customers successfully overcome these complex challenges. By implementing the core Govarix modules, our clients have already eliminated critical pain points such as data exfiltration risks, the manual burden of regulatory documentation, and the security blockers that previously prevented AI adoption in highly sensitive environments.

Learn more about Sphere →

Sphere Develops a New AI Maturity Assessment Tool

AI conversations are everywhere, but many organizations still lack a clear view of how ready they are to turn AI investment into measurable business value.

Sphere’s free AI Maturity Assessment is a 7-minute diagnostic that scores an enterprise across strategy, data, technology, talent, governance, and value realization. Results are benchmarked against IDC and Accenture data by industry and company size, giving teams a clearer view of where they stand and what to prioritize next.

The tool is currently in beta. Message us directly to request a passkey.

Request a beta passkey →

What to Read from Sphere

SphereIQ Saves 500 Hours/Month for a Texas Contractor

A Texas construction company with 120 employees, 17 years of operational data, and 8 core business systems deployed SphereIQ – Sphere’s custom AI assistant – in under two weeks. The system connects every data source the company runs on, answers employee questions in seconds, and enforces role-based access across the organization.

Read the case study →

The Rise of Physical AI: What Actually Works and What You Need to Know

Physical AI is getting serious attention, with investors backing software that can act as a “brain” for robots and machines operating in the real world. But the gap between lab demos and production reality is still wide.

This Sphere article breaks down what Physical AI actually means, where the technology is already working, and where the hype is running ahead of practical deployment. The real opportunity today is not general-purpose humanoid robots. It is focused, measurable applications in warehouses, manufacturing, logistics, healthcare, and other structured environments where AI-powered automation can solve specific operational problems.

For business leaders, the question is not whether Physical AI is coming. It is where it can create value now, what still needs time, and how to separate real ROI from market noise.

Read the article →

100 OpenClaw Use Cases You Can Try Today

OpenClaw is a persistent AI agent that runs on your own hardware, connects to large language models, and acts on the world – reading files, running commands, browsing the web, sending messages, and remembering everything you tell it. Visit openclaw.ai (opens in new tab) to learn more or go straight to docs.openclaw.ai (opens in new tab) to get started.

This guide answers that question with 100 real use cases across personal productivity, business operations, development, and creative work. Each one is described in plain language – what it does, why you’d want it, and which OpenClaw tools it needs. You don’t need all 100. Find the five that would change your week most and start there.

We’ve personally deployed or advised on more than 60 of these workflows. Where we’ve seen consistent patterns – good and bad – we’ve added observations throughout. These come from real production deployments, not theory.

Read the article →

Let’s Keep the Conversation Going

AI, data, and automation are moving fast, but the most useful conversations are still grounded in real business challenges.

Have a question, topic, or use case you’d like us to cover in a future issue? Send it our way. We’re always interested in what teams are building, testing, questioning, or trying to solve next.

Thanks for reading. We’ll be back next month.