There’s no shortage of discussion about the growing impact of rapidly advancing technologies, especially artificial intelligence, on businesses and the workplace. But emerging technologies can do more than boost productivity and reshape industries—they can also help address persistent social and environmental challenges.
Growing evidence suggests that AI and other technologies can support efforts to improve lives, protect resources and tackle problems that have long resisted easy solutions. Here, members of Forbes Technology Council discuss promising emerging technology use cases for addressing social or environmental challenges, along with what would need to happen for these solutions to scale effectively and responsibly.
AI-Powered Healthcare
AI has the potential to make high-quality healthcare accessible to far more people by supporting diagnosis, treatment planning and patient care. To scale responsibly, these systems need rigorous clinical validation, strong privacy protections and human oversight for critical decisions. – Alex Spokoiny, Check Point Software
AI-Driven Supply Chain Transparency
One promising use case is AI-driven supply chain transparency to help organizations identify emissions, ethical sourcing risks and supplier disruptions in real time. In my experience, the technology is already capable; what’s needed now is better data quality, common reporting standards and greater collaboration across supplier ecosystems to scale it responsibly. – Prajkta Waditwar, Box Inc.
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Agentic AI For Nonprofits
In the resource-strained nonprofit sector, agentic AI can move from supporting work to carrying it, helping fundraising teams stay consistently present, personalized and informed across more of the donor base without adding headcount. But responsible scale requires more than new tools. It requires trusted data, clear governance and transparent operating models that keep humans firmly in the loop. – Mike Gianoni, Blackbaud
Digital Twins For Smarter Infrastructure
AI-powered digital twins for energy and urban infrastructure could significantly reduce emissions by optimizing electricity grids, buildings and transportation networks in real time. To scale responsibly, organizations will need standardized, high-quality data; transparent decision-making; strong cybersecurity; and clear governance to ensure AI recommendations remain reliable, fair and accountable in critical infrastructure. – Taras Tymoshchuk, Geniusee
AI-Accelerated Advanced Materials Discovery
AI and high-performance computing could accelerate the discovery of advanced materials for cleaner batteries, carbon capture and low-emission industry. Responsible scale requires laboratory validation, transparent life-cycle analysis, secure research pipelines, ethical mineral sourcing and manufacturable economics—because a breakthrough matters only when society can safely deploy it. – Rajjie Sarmey, FutureProof CXO™
Programmable Payments For Humanitarian Aid
Programmable payments could transform cross-border humanitarian aid by releasing funds only after aid is delivered or predefined milestones are verified. Unlike instant payments, programmable payments embed compliance and transparency into each transaction. As agentic commerce grows, they become a foundation for trusted AI-enabled payments. Scaling responsibly requires interoperable standards, privacy safeguards, governance and human oversight. – Divyarani Raghupatruni, Alacriti Inc.
Digital Twins For Climate Resilience
AI-powered digital twins can transform climate resilience. By simulating floods, wildfires, energy demand and infrastructure stress, they can help governments and businesses make better decisions before disasters occur. To scale responsibly, they need transparent data governance, validated models and human oversight to ensure decisions remain accurate, equitable and accountable. – Ambarish Majumdar, Meta
AI Learning Companions
AI learning companions for children in areas that are difficult to staff with teachers can provide patient, personalized help in a child’s own language at near-zero cost. Scaling responsibly needs evidence gates that measure learning, not engagement; teachers in the loop as orchestrators; and child data that’s treated as untouchable. The aim is not replacing teachers; it is stopping geography from deciding who gets one. – Adarsh Sudhindra, Excelsoft Technologies Limited
Open Web Data For Investigations
Open public web data is becoming a powerful tool for investigative journalists tracking disinformation and evidence of financial crime and environmental harm that hides across thousands of scattered sources. Small newsrooms and NGOs often can’t gather this data at scale. To do this responsibly, we need shared open standards, clear ethical limits on what gets collected, and legal support so the people exposing wrongdoing are protected. – Julius Černiauskas, Oxylabs
AI Fit Tools To Reduce Retail Returns
For retailers, customer returns create a loss of revenue, but they are also a major contributor to environmental harm. AI-powered fit tools and try-on features can increase the likelihood of customer satisfaction and, in turn, reduce returns, minimizing unnecessary waste and emissions. To scale responsibly, retailers need to scrutinize customer data and operational capability while integrating these tools seamlessly into existing systems. – Brett Beveridge, The Revenue Optimization Companies (T-ROC Global)
AI To Detect Forced Labor Risks
AI-driven analysis of import, shipping, customs and trade data can flag forced labor risk deep in supply chains before goods reach the market. Most consumers never see where products truly originate. Scaling responsibly requires transparent data sourcing, visibility beyond direct suppliers and human review of flagged cases. – Yardley Pohl, interos.ai
AI-Powered Translation For Public Services
Real-time translation could help people access healthcare, housing, benefits and other government services in hundreds of languages. This would, of course, require extensive testing with native speakers and guaranteed human intervention when errors could potentially harm someone. – Amy Gu, Dynamsoft
Technology To Measure Technology’s Impact
Using technology to more accurately predict technology’s impact could go a long way toward changing the discussion and holding offenders accountable. This case holds especially true in areas like the mental health impact of social media or the climate impact of AI, where you need to analyze vast amounts of data to get a coherent picture. – Kevin Korte, Univention
Everything-To-Grid Energy Storage
An incredible use case is everything-to-grid (V2G) energy storage, which allows building backup systems and parked electric vehicles to automatically feed power back into overloaded electrical grids during peak demand. To scale responsibly, we must establish universal, open-source API standards and real-time automated validation loops to secure bidirectional data flows, protecting the physical grid from massive cybersecurity exploits. – Mahendran Chinnaiah
AI-Powered Precision Agriculture
AI can tell a farmer how much nitrogen each specific part of a field needs—not an average, but a location-by-location decision. This reduces cost and runoff. Scaling it responsibly requires field-level data infrastructure and human operators who can override what the model misses. – Joseph Byrum, Big House Enterprise
AI Forecasting To Reduce Food Waste
AI-powered demand forecasting could meaningfully reduce food waste by helping retailers better align inventory, pricing and replenishment with actual demand. To scale responsibly, it requires reliable data, interoperability across the supply chain, measurable outcomes and human oversight to prevent unintended impacts on availability and access. – Lori Schafer, Digital Wave Technology
Assistive Robots For Older Adults
Assistive robots that help older adults with mobility, lifting and daily tasks could ease a caregiver shortage that will only worsen as populations age worldwide over the coming decades. To scale responsibly, deployment needs input from the elders and family caregivers actually living with the tools day to day, affordability well beyond wealthy households, and clear limits so the robots extend independence rather than replacing the human contact people still need most. – Jagadish Gokavarapu, Wissen Infotech
Drones For Wildfire Response
The use of drones for fighting wildfires is a tremendous application of emerging technology. As we have seen in L.A., there is a critical window to respond to wildfires. Forward-deployed drones equipped with chemicals, cameras, sensors and so on can identify and slow the spread of wildfires. The results include saved lives, the savings of billions of dollars in direct damages and costs, and the prevention of environmental and community destruction that can take decades to repair. – Mark Francis, CaregiverZone
AI-Designed Proteins To Break Down Plastic
AI-driven protein design is enabling enzymes that break down plastic waste in hours, not centuries, turning landfills into recoverable raw materials. To scale responsibly, this initiative would likely require rigorous biosafety review, verified degradation byproducts, industrial pilot testing before mass release, and infrastructure to collect and sort waste so the enzymes reach the plastic that needs to be broken down. – Dan Sorensen, Nexus Security Advisors
