Corporate AI’s Growing Impact on the Potential for Global Economic Equity
Learn how organizations can prepare for AI-driven changes in the workplace.
Duri Chitayat, CTO of Safeguard Global, discusses how AI can drive a new era of innovation and productivity, transform organizational models, and create both opportunities and challenges in the workplace.
Technology can trigger large-scale change, and AI is about to tip us into a new era of work. In the same way, that the telegraph and steam power ushered in the Industrial Revolution, the recent wave of AI innovation will go beyond automation. AI is driving a new paradigm of innovation, productivity, and growth in the workplace.
By 2030, AI is expected to add $13 trillion to the global economy, boosting GDP growth by 16%. According to a Goldman Sachs Research report, already roughly two-thirds of U.S. jobs are experiencing a degree of AI disruption, and history shows that new tech can have wider effects, changing organizational operating models altogether. For instance, the emergence of generative AI platforms utilizing OpenAI’s ChatGPT architecture and deep learning techniques is revolutionizing access to information on employment legislation. Questions that once took days to answer can now be addressed within seconds, enabling companies to maintain comprehensive knowledge of HR and payroll topics, including benefits, compensation, hiring processes, and employee policies. Users can simply ask questions in natural language, enabling AI to generate accurate and relevant responses.
AI can be incorporated into a variety of strategic business functions, like recruiting to help identify top candidates, people analytics to help provide global workforce salary benchmarks, and software development to give software engineers AI programming assistance. In addition to its application in employment legislation, compliance, and the mitigation of potential liabilities, AI is increasingly playing a significant role in improving the speed and accuracy of many critical processes.
For instance, predictive maintenance and diagnostic streaming are enhancing productivity in manufacturing by preventing costly outages and unnecessary maintenance. By using AI to analyze streaming data for pattern recognition, organizations gain confidence in their operations’ safety and receive alerts before serious issues or hazards arise. Supply chain optimization has become paramount, particularly after the disruptions experienced in 2021. AI is now being used for running multi-scenario analyses, monitoring complexities in real-time, and making risk-weighted recommendations. Similarly, quality control has seen advancements through features like image recognition, data analytics, and the identification of defects before products leave factory floors. However, participation in the benefits of this wave of transformation is not guaranteed to benefit every person, organization, or region. There are significant adoption challenges that are not equally distributed.
Education and the Digital Divide
AI will enable organizations to automate roles that are heavily routine and rely on pattern recognition. And it’s interesting how many of our expert roles fall into that category. The 10,000-hour rule, popularized by Malcolm Gladwell in his book “Outliers,” posits a simple yet compelling idea: to achieve mastery in any field requires approximately 10,000 hours of dedicated practice. This concept suggests that expertise is often founded upon one’s ability to recognize patterns and perform routines with precision and speed. So, it is likely that our most educated will find significant disruption to their jobs. These include industries like Law, IT, and Healthcare.
At the same time, new challenges emerge that require orchestration, problem-solving, and creativity. Organizations adopting AI will face a talent gap for the new era of work. As organizations pursue AI adoption, talent gaps emerge where people capable of working in one model struggle to adapt to the level of complexity and speed the environment demands.
Individuals who are willing to dedicate themselves to continuous learning and development—effectively applying their own version of the 10,000-hour rule to the new era of work—are the ones most likely to excel and benefit from these changes. Online learning platforms, AI tutors, and educational apps can help to bridge the educational divide and offer personalized learning experiences. This democratization of education represents a critical step toward leveling the playing field, enabling more individuals to harness the opportunities that AI advancements bring.
The digital divide represents multifaceted challenges, encompassing not just access to high-speed internet, which is foundational for any digital activity, but also access to investment capital that fuels advanced technology development. Emerging and developing economies often lack both, limiting direct participation in the digital economy and stifling grassroots growth and innovation. Currently, AI innovation is heavily concentrated in large companies and regions like Silicon Valley due to certain technical foundations that accelerate AI adoption and innovation.
Large companies have amassed significant advantages over the years, including vast data stores for training AI models and sophisticated technical infrastructures. Access to top-tier talent, advanced graphics processing units (GPU), and other specialized hardware further raises barriers to entry into AI.
However, the landscape is not entirely bleak. Many existing infrastructures within large organizations require substantial overhaul to be optimally leveraged for AI. This necessity presents a unique opportunity for organizations with less legacy tech to leapfrog ahead by adopting cutting-edge AI solutions without the burden of outdated systems. Moreover, cloud platforms are democratizing access to computational resources, allowing organizations of all sizes to rent the necessary compute power for AI, leveling the playing field to a certain extent.
Open-source projects provide powerful AI tools and frameworks at little cost, enabling small organizations to harness AI’s capabilities without significant investment. This access not only fosters innovation but maintains the agility and potential inherent in smaller groups.
As these solutions continue to evolve, the possibility for more equitable participation in AI becomes increasingly tangible and suggests a future where the digital divide could be significantly narrowed, if not completely bridged.
Establishing Organizational Responsibility
These educational and infrastructure development challenges beg the question: is it a company’s responsibility to help its employees participate in the new era of work?
I believe it is in most organization’s interest to go beyond the deployment of technologies to enable systematic adoption by its people actively. Recent studies show successful AI adoption significantly boosts productivity, benefiting both highly skilled professionals and underemployed workers. Whether adopting AI makes workplaces more diverse, equitable, and inclusive will depend on the people implementing, training, and operating the technology – as well as the preparation of their teams long beforehand.
Advanced economies adopting AI more rapidly must prioritize agility and integration while developing robust regulatory frameworks to cultivate a safe and responsible environment. In emerging markets and developing economies, companies must lay a solid foundation by investing in the digital infrastructure, education, and resources needed to meet their objectives.
See More: AI Adoption: The Benefits of Upskilling vs. Hiring
Ensuring Equitable Implementation
AI must be integrated in ways that accommodate different economies, cultures, and varying digital accessibility. To achieve equitable implementation, companies can take the following steps:
- Conduct a comprehensive assessment with a focus on resource equity. Beyond identifying technological needs or skill gaps, companies must ensure that no employee, regardless of geographical location, is left behind in the digital transformation journey. An AI practitioner in India should have the same access to the proper resources, training programs, and equipment, such as laptops and specialized software, as their counterparts in the U.S. or Canada.
- Invest in infrastructure development. Companies should consider collaborating proactively with local governments, non-governmental organizations (NGOs), and other stakeholders to invest in infrastructure development projects. Helping to expand broadband access, enhance electricity supply, and upgrade communication networks to narrow the digital divide will go a long way in enabling all operating regions to benefit equally from the advancements AI brings to the global economy.
- Offer training and upskilling programs. Create opportunities for employees to engage with AI. Newer platforms often involve complex processes, such as machine learning and model development, and don’t fit easily into a typical workflow. Learning to use them requires a fresh approach to training, not just adding them as another tool in their toolbox. At Safeguard Global, we’ve successfully experimented with a method we call “dojos”—dedicated groups for practicing exercises and simulations that are focused on learning rather than achievement.
- Foster collaboration and knowledge sharing across regions and departments. These actions are essential to encourage collective learning and innovation, break down silos and democratize access to AI knowledge. By leveraging cross-functional teams and workshops, companies can accelerate AI adoption and foster a supportive community.
- Monitor progress and adapt strategies. Companies must continuously monitor and update their training programs to keep pace with system updates. Regular evaluation and integration of new learnings ensures the workforce remains current and adaptable. Frequent feedback, performance assessments, and agile strategy adaptation are crucial for implementing AI effectively and maintaining a competitive edge.
AI is a Catalyst for Digital Maturity in Underserved Markets
AI presents opportunities to bridge the tech infrastructure gap and empower employees in underserved markets. Those in roles AI enhances must invest a percentage of their time in learning how to use it. Those more advanced, who are enthusiastic and proactive about AI, will be invaluable in guiding others.
By investing in training initiatives and leveraging AI-driven solutions, companies can bridge the tech infrastructure gap, unlock new growth for themselves and their teams, and create a more inclusive and prosperous future for all.
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