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America’s hydrogen-fueled future stalls over tax credits

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2 years ago

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Inside Plug Power's Liquid Green Hydrogen Plant In Georgia
Hydrogen is loaded into a truck at the Plug Power Inc. liquid green hydrogen plant in Woodbine, Georgia.

Agnes Lopez/Bloomberg

Two years after President Joe Biden’s landmark climate law promised to kick-start green hydrogen production with generous tax credits, companies still don’t know who will qualify. 

Billions of dollars in investments sit on the sidelines as a result. 

The Biden administration sees green hydrogen as a critical component of the energy transition, a way to clean up heavy industries that can’t easily run on electricity. But the nascent hydrogen economy has been paralyzed waiting for final rules on a key tax credit, which will provide up to $3 for every kilogram of the fuel produced. 

Hydrogen companies considered the initial guidelines issued by the Treasury Department late last year too strict and warned that many of their planned plants wouldn’t qualify for the full incentive. Developers have since been left in limbo as they await adjustments before the final rules are approved. 

Hy Stor Energy, for example, plans to produce hydrogen in Mississippi using on-site wind and geothermal energy and be operational in 2027.

“Our project has multiple gigawatts of renewables and is holding off billions of dollars in investment,” said chief commercial officer Claire Behar. “That is just one project. If you multiply it by 10 to 20 projects, it’s a massive investment that’s being stalled.”

The delay isn’t simply a case of slow-moving bureaucracy. Industry and environmentalists have engaged in a months-long lobbying fight over the rules, with the federal government trying to strike a balance. But the lack of progress could impede the nation’s decarbonization efforts.

“People in the industry are very frustrated,” said Frank Wolak, chief executive officer of the Fuel Cell and Hydrogen Energy Association. “The longer people defer investments, the less committed they are.”

Almost all hydrogen produced today is stripped from natural gas in a process that gives off carbon dioxide. But there are cleaner ways to make the fuel, such as capturing the CO2 or splitting the hydrogen from water using renewable electricity. Those cleaner methods are the focus of the Inflation Reduction Act tax credit. The size of the credit available to each project rests on three so-called pillars: ensuring hydrogen is produced using new clean energy sources rather than existing ones, aligning hydrogen production with electricity generation times and adhering to stringent carbon intensity requirements. 

Without strict rules on each, environmentalists argue, hydrogen production plants risk driving up greenhouse gas emissions rather than cutting them. 

“The first draft in December was an excellent framework that will attract the truly green projects,” said Fred Krupp, president of the Environmental Defense Fund. “Whatever happens, it’s critical that Treasury uphold this framework and not add exemptions that would water down the emissions integrity.”

Companies counter they need looser rules, at least at first, to get the industry off the ground. 

In addition to the tax credits, the federal government has set aside $8 billion to create a series of hydrogen hubs that would match producers of the fuel with customers using it. But leaders of the regional hubs are so worried about the current tax credit guidance that they sent the Treasury Department a letter in February arguing many of their own projects won’t happen unless the rules are changed. The hubs, they said, are expected to generate $40 billion in private investment and support 334,280 jobs.

“Unfortunately, these investments and jobs will not fully materialize unless Treasury’s guidance is significantly revised,” they wrote.

The Treasury Department says it is carefully considering all the many comments it has received as it drafts the final rules, but officials haven’t given any timeline for finishing the work. “Finalizing rules that will help scale the clean hydrogen industry while implementing the environmental safeguards established in the law remains a top priority for Treasury,” a department spokesperson said in an email. 

Finding the right balance has been hard. John Podesta, Biden’s senior adviser for international climate policy, called the IRA’s hydrogen incentives “the most complex of the credits, technically and legally” at an event this week celebrating the second anniversary of the law’s passage. He acknowledged the mixed reaction the government’s preliminary guidelines received. “Some people loved it,” Podesta said. “Some people didn’t.”

Even if new guidelines are published now, companies might wait until after the election to see if they need to comply with them, according to Martin Tengler, an analyst at BloombergNEF. Donald Trump has promised to target the IRA if he retakes the White House in November, but his attitude toward hydrogen is unclear. 

Policy uncertainty is not confined to the US. German company Thyssenkrupp Nucera in July abandoned its 2025 forecast for its business selling electrolyzers, the machines that split water into hydrogen and oxygen. 

“Progress on the regulatory side is recognizable, but at the same time not yet sufficient to accelerate investment momentum again,” Thyssenkrupp Chief Executive Officer Werner Ponikwar said in a statement. “The result is further delays to new projects on the customer side.”

Rival Siemens Energy AG has invested €30 million to produce electrolyzer stacks in Berlin together with industrial gas company Air Liquide. 

“In the short term, we do observe delays in the release of funding commitments due to regulatory uncertainties, for example in the US and in Europe,” Chief Financial Officer Maria Ferraro said in an analyst call in May. Long-term prospects for the business, however, remain intact, she added. 

Some in the industry expect the Treasury Department to soften its rules — although that hasn’t happened yet. Andy Marsh, CEO of Plug Power Inc., said he expects new guidance soon.

“We won’t be surprised if there’s some announcement after the Democratic convention and a further announcement after the election,” he said during the company’s earnings call last week. “I think it’s really clear that the regulations on the three pillars are going to become much looser.”

Carbon-free green hydrogen remains far more expensive than hydrogen from natural gas, and until that changes, companies have little incentive to start using it as a fuel. But costs won’t come down until the wave of planned green hydrogen plants start opening, Tengler said. And they won’t move forward until the federal government finalizes its tax rules.

“The only way green hydrogen becomes cheaper is by building projects, but with these early projects stalled, the industry is being choked before it’s even born,” Tengler said.

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Accounting

AI-Driven Automation and Continuous Accounting Frameworks

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10 hours ago

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August 15, 2026

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The accounting profession is undergoing a fundamental structural transition as enterprise finance departments shift from periodic month-end closes toward automated continuous accounting models. By integrating specialized machine learning algorithms directly into enterprise resource planning (ERP) platforms, chief accounting officers are transforming financial reporting from a retrospective exercise into a real-time operational asset.

The Shift from Periodic Close to Continuous Financial Reporting
Traditional accounting workflows heavily relied on manual data reconciliation, spreadsheet calculations, and multi-week closing cycles at the end of each fiscal period. In contrast, continuous accounting frameworks utilize automated software agents to process, validate, and post transactional data in real time as business activities occur.

Automated bank reconciliation tools cross-reference incoming bank feeds, invoice records, and purchase orders automatically. By resolving transactional variances instantly throughout the month, corporate accounting teams eliminate the traditional workload spikes associated with quarterly and annual closes.

Machine Learning in Audit Trails and Anomaly Detection
Advanced natural language processing (NLP) and machine learning tools are redefining internal audit and financial control environments. Automated systems analyze 100% of general ledger entries, identifying anomalous transactions, duplicate payments, and unauthorized journal entries in real time.

Rather than relying on random statistical sampling, corporate internal auditors can focus their attention on high-risk flags automatically surfaced by algorithmic monitoring platforms. This continuous risk assessment strengthens internal controls over financial reporting (ICFR) and significantly reduces fraud risk.

Evolving Roles for Accounting Professionals
As routine data entry and manual reconciliation tasks become fully automated, the skill set required for accounting professionals is shifting toward data analysis, system design, and strategic business advisory.
– Systems Governance: Accountants are increasingly responsible for monitoring algorithmic accuracy and managing data integration pipelines.
– Business Partnership: Finance professionals leverage real-time financial dashboards to advise operational leaders on margin management and working capital allocation.
– Regulatory Compliance Management: Accounting teams utilize automated platforms to ensure compliance with dynamic tax codes and international accounting standards.

Core Implementation Recommendations
1. Deploy Automated Reconciliation Tools: Integrate continuous transaction processing modules into existing enterprise ERP architectures.
2. Establish Algorithmic Governance Controls: Implement strict internal testing protocols to ensure automated accounting rules comply with GAAP/IFRS standards.
3. Reskill Accounting Teams: Invest in training finance staff on data analytics, workflow automation, and predictive financial modeling.

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Accounting

Global ESG Reporting Standards and Double Materiality Compliance

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6 days ago

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August 9, 2026

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Corporate accounting departments face expanding reporting expectations as international sustainability disclosure standards achieve regulatory enforcement across major global jurisdictions. Chief Accounting Officers (CAOs) and corporate controllers are establishing rigorous internal accounting controls to treat Environmental, Social, and Governance (ESG) metrics with the same data precision, auditability, and governance as traditional financial statements.

Regulatory Harmonization Under Global Sustainability Frameworks
The implementation of standardized sustainability reporting frameworks—notably rules established by international sustainability accounting boards—has created unified expectations for public and large private enterprises. Corporations must report standardized metrics covering greenhouse gas emissions (Scope 1, 2, and material Scope 3), energy utilization, workforce demographics, and supply chain governance.

In Europe and other participating international jurisdictions, double materiality principles are mandatory. Under double materiality, organizations must report both how external sustainability risks impact corporate financial performance, and how internal corporate operations affect surrounding environmental and social structures.

Integrating Sustainability Metrics into Core ERP Systems
To provide auditable non-financial data, enterprise organizations are integrating specialized carbon accounting and ESG management platforms directly into core ERP systems. Automated data collectors capture energy utility invoices, logistics fuel consumption metrics, and vendor compliance records in real time.

Establishing automated, traceable data pipelines ensures that non-financial reporting is supported by clear audit trails. This structured approach allows external financial auditors to provide reasonable assurance on sustainability disclosures during annual corporate reporting cycles.

Financial Impacts and Capital Market Disclosure
Accurate ESG reporting directly influences corporate cost of capital and institutional credit ratings. Commercial lenders and institutional asset managers systematically incorporate sustainability metrics into risk pricing models. Companies that demonstrate transparent, verifiable progress in operational energy efficiency and climate risk mitigation benefit from expanded access to green bond markets and lower debt pricing.

Action Steps for Accounting Leadership
1. Implement Double Materiality Frameworks: Conduct comprehensive assessments to identify material financial and operational sustainability metrics.
2. Build Auditable Non-Financial Data Pipelines: Automate ESG data collection within core accounting software to ensure data integrity.
3. Align Sustainability with Annual Financial Filings: Prepare non-financial disclosures concurrently with financial statements to satisfy regulatory audit expectations.

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Accounting

Modernizing Internal Controls: Machine Learning and Continuous Monitoring in Auditing

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1 week ago

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August 5, 2026

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Internal audit departments and corporate risk managers are modernizing internal control frameworks by shifting from periodic sampling techniques to continuous monitoring and machine learning analytics. As operational data volumes increase across enterprise organizations, automated control testing ensures financial integrity, prevents corporate fraud, and streamlines annual audit engagements.

The Limitation of Periodic Audit Sampling
Historically, internal and external auditors evaluated internal controls by reviewing random samples of financial transactions—often analyzing less than five percent of total ledger entries. In complex enterprise environments, periodic sampling methods carry inherent risks of overlooking localized financial misstatements, unauthorized disbursements, or operational control breakdowns.

In 2026, progressive internal audit functions are utilizing automated continuous monitoring platforms that evaluate one hundred percent of financial transactions in real time. Continuous control auditing systems continuously monitor general ledger entries, procurement approvals, and expense reimbursements across all operating subsidiaries.

AI-Powered Fraud Detection and Anomaly Identification
Machine learning models trained on historical corporate financial data excel at identifying subtle transactional anomalies that indicate potential fraud or operational error. Automated systems instantly flag duplicate invoice payments, unapproved vendor creation, unusual journal entry timing, and unauthorized override of authority thresholds.

When an anomaly is detected, the automated auditing platform generates an instant risk alert, allowing internal audit teams to investigate root causes immediately. Early detection prevents minor operational errors from escalating into material weaknesses in financial reporting.

Streamlining External Audit Preparation
Continuous internal control monitoring delivers significant benefits during annual external financial audits. External audit firms can review continuous audit logs and automated control testing documentation, reducing the time required for manual field testing.

This integrated approach lowers overall audit compliance fees, reduces administrative burdens on corporate accounting staff, and provides senior management and audit committees with real-time visibility into the organization’s overall risk profile.

Core Implementation Guidelines
1. Transition to 100% Data Testing: Replace legacy sampling methods with automated continuous audit monitoring systems.
2. Deploy Anomaly Detection Algorithms: Implement machine learning models to identify unauthorized transactions and operational control overrides.
3. Align Internal and External Audit Workflows: Coordinate continuous control testing protocols with external auditors to optimize annual compliance cycles.

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