Anthony Hoang

Anthony Hoang is a technology leader who believes the most meaningful work of his nearly three-decade career — including leadership roles at Target, Bridgewater Associates, and Evereve — has come from putting people and mission at the center of technology. As CTO at CleanChoice Energy, he applies that philosophy at the intersection of climate, the U.S. energy grid, and AI, leading technology strategy and AI-driven digital and data transformation across three distinct businesses: a leading direct-to-consumer clean energy brand, a utility-scale solar generation platform, and a renewable-energy trading desk. His conviction and the vision guiding his teams is that mission-driven organizations equipped with the right human-AI operating model can move faster and create greater impact than most expect.

Leading Technology Across Diverse Businesses

As CTO at CleanChoice Energy, I serve as a technology, innovation, and transformation partner across the organization, working closely with the CEO, consumer energy business leaders, solar development teams, and leaders operating what is effectively a renewable-energy trading desk.

Throughout my career, I have thrived where technology plays a strategic role in how businesses compete and grow. Experiences at Target, Bridgewater Associates, and Evereve reinforced the importance of aligning digital and data strategies with business objectives. Today, my focus is helping organizations harness increasingly complex data to make better decisions and accelerate transformation.

Over the last 12–18 months, AI has become central to that mission. Having started my career as a software engineer during the dot-com era, I recognize a similar level of disruption and opportunity. Those experiences continue to shape how I evaluate innovation and the transformative impact AI is having across industries.

Building Resilient Energy Technology Systems

At CleanChoice Energy, several major technology initiatives have required building specialized teams around highly complex operational challenges. One of the largest areas of focus has been strengthening our direct-to-consumer technology stack and creating customer engagement across digital platforms, in-person sales channels, and traditional marketing ecosystems. I have centered much of that strategy around data, using platforms such as Braze, Segment, commerceTools and Salesforce to improve engagement and operational visibility.

Another major initiative involved modernizing the back-end infrastructure that enables CleanChoice to operate within the U.S. electric utility ecosystem. This became the company’s largest technology transformation because it required maintaining uninterrupted machine-to-machine integrations with more than 40 utilities while redesigning critical systems. Executing that transition without disrupting live customer operations demanded resilient engineering and disciplined governance.

A current priority is managing energy volatility. To respond, we are building a dynamic renewable-energy trading desk supported by real-time market signals, demand data, and AI-augmented risk analytics to protect both the business and the households we serve.

At the same time, expansion of our solar fleet has created new infrastructure challenges. We operate utility-scale solar facilities spanning hundreds of acres, where equipment must withstand weather, dust, and heat while continuously capturing real-time signals from panels, inverters, and trackers. We have built ground-to-cloud infrastructure connecting every site to a centralized control plane, enabling a small operations team to monitor and act across the entire portfolio.

Scaling Trust Through Data Infrastructure

Data plays a foundational role in nearly every aspect of how we operate and make decisions at CleanChoice Energy. Over the last several years, we have made significant investments in building a scalable data infrastructure, including partnerships with Snowflake and Amazon Web Services to create a centralized data lake environment, along with master data management systems like Reltio.

More recently, the focus has shifted toward harnessing and enriching that data more effectively. We integrate information from multiple third-party sources that support areas ranging from energy market intelligence to solar utility operations. What has become especially valuable is the emergence of AI-powered data governance and AI-driven metadata creation, which has significantly improved our ability to scale transparency across the business.

We combine Anthropic Claude, Glean, Snowflake Cortex, and Domo to democratize data access, enabling customer-care supervisors, risk analysts, and solar-operations leaders to interrogate large datasets through natural language without relying on analysts or engineers. We are also investing in metadata, context data engineering, and governance—the disciplines that determine whether an agentic framework scales successfully.

The impact extends across operations, marketing, finance, trading, and HR: finance runs scenarios that once took a quarter, trading closes loops between market signals and risk faster than human cycles allow, marketing iterates campaigns faster, and HR is rethinking talent acquisition.

AI is doing two things at once: putting unprecedented demand on the U.S. energy grid, and giving us the operating model to meet it. The system gets more agentic, the human gets more human. The companies that internalize this change will define what renewable energy looks like in the decade ahead.

Turning Market Volatility into Operational Advantage

A significant part of maintaining reliable and scalable technology solutions comes from the level of investment we make in data engineering. Technology partnerships also play a major role in that success. We work closely with platforms such as DBT and Matillion, alongside specialized providers including Beacon for risk data management and Canary for energy utility IoT data. These technologies form a highly sophisticated data ecosystem that supports multiple areas of the company.

What matters most is having a clear strategic vision for how all these systems and partners work together to solve very different business challenges across our consumer, generation, and power trading operations. That alignment has helped us adapt as the energy market continues to evolve rapidly.

Volatility in energy pricing is increasingly affecting households, with utility bills becoming a larger share of monthly expenses. A major priority for me is ensuring our technology capabilities allow the business to respond quickly to those market shifts while positioning us to create greater efficiency and long-term savings for customers.

Creating Cultures Where Teams Expand

For most leaders, the hardest challenge is not the technology but the mindset shift. AI began as an assistant used to draft emails, summarize documents, or retrieve information. Agentic AI is different: an agent owns an outcome. Leaders define inputs, quality standards, and escalation rules, while the agent determines the steps. That represents a fundamental change in management.

The best analogy comes not from technology but from leadership. An orchestra conductor does not play every instrument, and a head chef does not cook every dish. Their role is to shape the ensemble, define responsibilities, set the tempo, and maintain standards. Management in an agentic organization works the same way. Designing an agent’s role has become as important as writing a job description.

The most compelling aspect, however, is the human impact. When repetitive work is removed, people spend more time on what they were hired to do. Analysts focus on analysis, marketers on creativity, and engineers on design rather than routine tasks.

That sense of meaningful work is what makes technology leadership transferable across industries. Whether in retail, financial services, fashion, manufacturing, or renewable energy, the satisfaction is the same: helping talented teams turn complexity into outcomes that matter for customers, businesses, and themselves. Practices such as demos, retrospectives, and open collaboration strengthen culture and connections across teams.

AI has brought unprecedented momentum to technology leadership. Across our organization, AI-augmented workflows have accelerated delivery. Between Q4 of last year and Q1 of this year, departmental output increased by nearly 50%, while some teams doubled productivity through AI-assisted engineering practices. As I tell our teams, we did not wait for the perfect power sander before stopping manual floor scraping; the right approach with agentic AI is to deploy it now and learn in motion.

The larger story is what those gains unlock. Work that once seemed too expensive is now worthwhile: reviewing every contract instead of sampling, monitoring every customer interaction instead of auditing a subset, and running analyses previously deprioritized. We have moved from sampling to census.

Looking ahead, I believe the energy companies that succeed over the next decade will treat AI not as a productivity layer attached to existing workflows, but as a new class of teammate capable of absorbing operational complexity, responding to volatility in real time, and enabling small, mission-driven teams to operate at the scale of much larger organizations. That is the future we are building at CleanChoice Energy. The system becomes more agentic, the human becomes more human, and the organizations that embrace both trends will define the future of clean energy.