As artificial intelligence transforms industries, its transformative potential is beyond the reach of many. While AI is revolutionizing healthcare, education and financial services, access to these advances is often limited to large enterprises and advanced economies. Bridging this digital divide is not just a technical challenge, but a social imperative.
Few people understand it better than this Sulakshana Singhis a senior software engineer at Equifax Workforce Solutions, who brings more than 14 years of experience to the role, and an AI ethics advocate committed to bringing the benefits of AI to underserved communities. His work at Equifax Workforce Solutions was instrumental in developing a scalable microservices architecture that improves workforce analytics by optimizing data processing and decision-making frameworks. By ensuring the transparency, security, and accessibility of enterprise solutions, he supported the adoption of responsible technologies—a commitment that earned him recognition as an IEEE St. Louis Chapter. Outstanding Woman in Engineering Award recipient
“AI doesn’t just have to be powerful, it has to be fair,” stresses Sulakshana. “We have a duty to make AI work for everyone.”
The digital divide in AI adoption
Despite the rapid growth of artificial intelligence, access remains limited for many businesses and individuals due to infrastructure gaps, high costs and lack of digital literacy. A report by The Wall Street Journal highlights that the increased use of AI will strain data centers and power grids as well as the country’s grid capabilities due to the high bandwidth and low latency requirements of AI workloads. This suggests that many organizations may not have the necessary infrastructure to effectively implement AI solutions. For enterprises in emerging economies or small businesses lacking AI expertise, integration remains an uphill battle.
Sulakshana has worked extensively in democratizing the adoption of AI, especially through cloud based AI models that reduce the cost of implementation. By promoting a multi-cloud architecture, he ensures that AI systems are scalable and affordable, making them viable for mid-sized enterprises, non-profits and emerging markets beyond the tech giants.
“Cloud and AI must work together to reduce barriers to entry,” he said. As a author published on Hackernoonhe explores the role of log analytics in cloud environments, highlighting how structured debugging and real-time monitoring are critical to ensuring reliable AI deployment. In a microservices-based AI architecture, log analysis plays an important role in detecting failures, optimizing system performance, and maintaining transparency, which are key factors in democratizing AI access for enterprises of all sizes. By improving observation and troubleshooting in AI-powered applications, he reinforces the importance of building sustainable, accessible and efficient digital ecosystems that support the equitable adoption of AI.
As AI systems make more decisions that affect human lives, bias, data privacy, and accountability have emerged as major concerns. If AI is built on skewed data or trained without diverse representation, it risks reinforcing inequalities rather than solving them.
Sulakshana is a strong proponent of Explainable AI (XAI) – ensuring that AI decisions are transparent, interpretable and free from bias. As an IEEE IoT Technical Reviewer, he plays a key role in evaluating AI and IoT research to ensure security, fairness, and transparency in emerging technologies.
“AI is only as good as the data it learns from,” he said. “We need to constantly check the models to ensure fairness and eliminate bias.”
Ways to overcome the digital divide
Bridging the AI access gap requires affordable adoption, workforce training, and ethical development of AI. Cloud-based AI solutions and open-source frameworks like TensorFlow Lite reduce costs, allowing startups and small businesses to integrate AI without heavy infrastructure investment.
Beyond accessibility, AI must solve real-world problems. In healthcare, AI-powered telemedicine platforms connect rural patients with doctors through artificial intelligence. In finance, AI-powered lending will expand access to credit to poor communities by breaking down traditional banking barriers.
Sulakshana actively supports these initiatives. promoting AI ethics, cloud computing and automation in professional development programs. In a recent interview, he discussed how AI is revolutionizing the software development lifecycle and emphasized the need for transparency in artificial intelligence and the ethical deployment of AI-powered tools. His work in improving CI/CD pipelines, bias reduction and artificial intelligence testing underscores his commitment to building scalable and responsible AI solutions that support both enterprises and developers in adapting to the future of work.
Sulakshona looks to the future and envisions a future where AI is not just an enterprise tool, but a fundamental factor in economic and social mobility. Whether through AI-based learning platforms, microfinance solutions or public sector AI initiatives, he believes that AI can empower communities, not just corporations, but only if it is built and implemented responsibly.
“The success of AI will not be measured by what it can do, but by who it benefits,” he concludes. “We have the opportunity to make AI a tool for global progress, not just a luxury for a select few.”
With leaders like Sulakshana driving change, AI is poised to not only transform industries, but also narrow the digital divide and create a more inclusive tech future.
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