News Spotlight

Telecommuting enhances adaptability to climate change. Aside from the immediate safety of employees, Hurricane Milton disrupted connections that worry companies whose remote workers relocated to the state (Bloomberg).

Employees hate their jobs because they lack purpose. Poor management, your relationships with coworkers, and your employer's commitment to social responsibility play a significant role in how negative your job experience feels (Business Insider).

DEI will look vastly different in 2025. As criticism of DEI efforts grows, companies are under pressure to modify their initiatives and the existing DEI model has required re-evaluation for some time (Fast Company).

Stat of the Week

A new report finds that 13% of retirees plan to go back to work in 2025, 22% are currently working and 38% don’t plan to retire for at least five more years.

The trend of more retirees returning to the workforce has several significant implications for the economy and society. This shift can help alleviate labor shortages in various industries, contributing to overall economic stability and growth. It can provide retirees with supplemental income, enhancing their financial security and quality of life. However, it may also create challenges, such as potential age-related biases in hiring and competition for jobs with younger workers. This trend can impact retirement planning and social services, as increased workforce participation among retirees could influence policies related to pensions and healthcare.

Deep Dive Article

Could AI be Key to Hitting Organizational Sustainability Goals?

Sustainability is top of mind for most individuals, organizations, and governments, and its importance is only increasing. The World Economic Forum estimates climate change is costing the world $16 million per hour, which gives a sense of the urgency of the issue.

Organizational leaders are feeling the stress, with 76% of the C-suite saying their company is under pressure from investors or other stakeholders to focus on sustainability. That’s according to the latest research from my company, Workplace Intelligence, in partnership with edX, the global online learning platform developed in 2012 by Harvard and MIT.

There are many challenges to hitting corporate, national, and global sustainability goals, not least of all a shortage of talent with the required skills. That leaves companies under-resourced when it comes to prioritizing crucial sustainability decisions.

With Artificial Intelligence (AI) also the center of many tech and workplace conversations, it’s time to explore the key ways AI can help organizations meet their sustainability objectives.

My new study with edX found that 75% of the C-suite say their company will not be able to achieve its sustainability goals without AI. However, few executives know how to do this effectively, with 65% admitting they have no idea how to operationalize AI to support sustainability at their company.

The good news is, that there are already pioneering projects underway that we can learn from, and opportunities for C-suite and employees to make the most of educational resources that enable individuals to connect the dots between AI tools and sustainability. However, few employees have access to this type of training and development.

In our research, nearly three out of four C-suite respondents said they have taken training on how AI can support sustainability, but less than a third of employees said the same. Yet over half (55%) of employees want that training, showing a clear opportunity to close the sustainability skills gap across the workforce.

When it comes to environmental sustainability, there are many ways AI can support organizational goals, from predicting resource usage and analyzing climate data to developing sustainable products and tracking regulatory changes. My company’s new research with edX even finds opportunities for AI to support the human side of sustainability, by identifying ways to improve employee well-being.

Nearly all C-suite respondents (96%) whose companies are using AI for this purpose report that it has improved their progress on sustainability goals and initiatives.

The path toward a more sustainable future is complex, and business leaders will need every tool in their arsenal to tackle the increasingly urgent pressure for reduced emissions, pollution, and waste. There is a significant opportunity for AI to support in this area, but optimizing its use requires upskilling not just leaders but also employees to help drive meaningful change.

In today’s article, I’ll outline three specific examples of AI-supported sustainability efforts. Let’s take a look.

1. Predict Energy Output and Usage

Real-time intel on energy production and consumption would be incredibly labor-intensive and expensive if organizations relied on people to do the monitoring and reporting. However, AI can support this in a number of ways. Firstly, AI can analyze past usage data to predict future output or needs and can identify opportunities to improve energy efficiency.

Secondly, AI-powered systems can continuously analyze data from sensors and devices to enhance the efficiency of energy usage, water consumption, and resource management, helping minimize waste and reduce carbon footprints.

For example, AI can predict energy output in renewable energy systems — such as forecasting solar and wind energy generation based on weather patterns — allowing companies to adjust their energy use accordingly. It can also improve energy storage by predicting peak usage times and managing battery charge and discharge cycles for greater efficiency.

Case study: Renewable energy company AES implemented an AI solution that reduced customer power outages by 10% and resulted in $1 million in annual savings.

In hydroelectric power generation, water serves as the fuel, and its availability depends heavily on rainfall. Operators like AES face decisions on when to use this resource, choosing to run water through turbines to produce electricity based on fluctuating market conditions.

By leveraging AI to analyze data — including reservoir levels, rainfall forecasts, operational costs, and regional electricity demand — AES optimizes the timing and volume of its power bids. This data-driven approach helps them maximize revenue while aligning energy production with market needs, creating both economic and environmental benefits.

2. Identify Sources of Pollution

Beyond energy efficiency, reducing pollution is a critical part of slowing climate change. AI tools can support in monitoring and detecting emissions and pollution levels so the appropriate measures can be implemented.

For example, AI-powered drone technology equipped with advanced environmental sensors enables businesses to perform real-time aerial inspections of their operations, pinpointing sources of pollution and evaluating their ecological impact.

This proactive method enables companies to swiftly address environmental concerns, maintain compliance with sustainability regulations, and reduce their overall carbon footprint. Additionally, AI can analyze the collected data to predict potential pollution hotspots, allowing businesses to implement preventive measures before problems arise.

Case study: Duke Energy, one of the country’s largest energy-holding companies, implemented a new AI-driven platform that uses satellite and ground-level sensors to detect methane emissions in near-real time.

Traditionally, natural gas utilities relied on estimates for emissions reporting due to limited monitoring capabilities. Duke Energy’s new platform radically increases the identification of leaks and the speed of response. AI and analytics process the data, providing actionable insights via clear dashboards, and precise geolocation means workers can quickly address issues. As the platform expands, it will support Duke Energy’s goal of achieving net-zero methane emissions by 2030.

3. Monitor and Optimize the Supply Chain

According to the UN’s 2021 Sustainable Transport Conference, the transport sector is responsible for approximately a quarter of global greenhouse gas emissions. Some of these emissions can be reduced or even eliminated simply by implementing more efficient routes and logistics, but no one person can understand an entire complex supply chain system. That’s where AI comes in to help identify opportunities for improvement.

From inventory optimization to reducing excess stock, to streamlining transportation and improving collaboration between factories and suppliers, AI-driven tools are already improving supply chain efficiency. AI can even forecast demand more accurately, allowing manufacturers to adjust production schedules and inventory levels to prevent overstocking or stockouts.

It can also optimize transportation routes by finding the most efficient routes — including analyzing traffic patterns and weather conditions — reducing fuel consumption and emissions.

Case study: This type of AI intervention is out of its infancy and already having a national impact. Walmart has successfully used its AI-powered Route Optimization to streamline its supply chain, reducing emissions and improving product availability. This award-winning solution helped the retail giant eliminate 30 million unnecessary miles and avoid 94 million pounds of additional CO² emissions.

Reducing the Sustainability Burden

With the majority of C-suite leaders reporting that they’re concerned about their organization’s ability to move the needle on sustainability goals, anything that can help alleviate pressure is going to be welcomed by the business world — and AI represents a clear opportunity. Beyond the three examples above, AI can be used to optimize maintenance, track regulatory changes, analyze sustainability data, and more.

However, making the most of these new tools and technologies requires training and development for both leaders and employees. With access to the right educational resources, an upskilled workforce will accelerate time to implementation, ensuring every organization can meet and exceed its sustainability objectives.

Thanks for reading — be sure to join the conversation on LinkedIn and let me know your thoughts on my company’s new research with edX.

Quote of the Week

“Success is the sum of small efforts repeated day in and day out.”
​Robert Collier