Silicon Meets Synapses: The New Era of Human-AI Collaboration

As artificial intelligence (AI) continues to evolve, a new paradigm is emerging that views AI not as a replacement for human intellect, but as its amplifier. This shift in perspective is reshaping the narrative around AI's role in the workplace and society at large, driving the path to the future of work.

The AI-Human Collaboration

Intelligence amplification, a concept pioneered by Douglas Engelbart in the 1960s and further developed by John Markoff in his book Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, presents a compelling vision for AI integration in the workplace. This approach offers a middle ground between fears of job displacement and the drive for efficiency by enhancing human capabilities rather than replacing workers entirely through creating collaborative human-AI systems, redefining job roles, and investing in employee skill development. With 73 percent of US businesses having adopted AI or planning to do so, according to PwC’s 2023 Emerging Technology Survey, boards should evaluate their own companies’ AI adoption strategies. 

While AI often boosts productivity significantly, its true potential lies in elevating the quality of work from good to exceptional, according to insights from the World Economic Forum’s “Boosting Productivity Is Only the Sideshow for AI: Transforming Good Work Into Great Will Be Its Real Benefit.” Boards should focus on developing a strategic AI value map to identify high-impact business areas across organizations’ value chains, rather than pursuing siloed use cases, to achieve transformative results. This approach should consider the five AI evolutionary capabilities—from AI as a general-purpose tool to autonomous AI agents—and map them to specific value chain activities, considering factors such as value creation, cost management, data availability, and required skill sets for successful implementation.

By implementing this strategy, boards can guide their organizations to preserve employee autonomy and dignity while boosting productivity, ultimately achieving transformative results through AI adoption.

Tailoring AI to Human Needs

Don Norman advocates for integrating AI into work routines with human preferences in mind in his book Design for a Better World. He suggests that AI should handle tasks categorized as dull, dangerous, or dirty, which he refers to as the “three Ds”, freeing humans to focus on more engaging and challenging activities.

When implementing AI systems, boards should establish an AI council that involves both board-level oversight and management participation that will carefully calibrate the level of AI autonomy based on risk assessments and potential value creation. In high-risk scenarios, such as AI-supported critical decision-making processes, human oversight remains crucial. Conversely, in low-risk, high-value situations, AI can take a more prominent role. It's important for boards to recognize that AI taking full control in certain contexts can be highly beneficial when appropriately implemented. The key for the AI council is to determine the appropriate level of autonomy for each application, ensuring that AI's capabilities are leveraged optimally while maintaining necessary safeguards. 

The Stanford Institute for Human-Centered Artificial Intelligence recommends thinking beyond user-centric design to embrace community-centric and society-centric approaches. This broader perspective considers the wider implications of AI integration, including its impact on organizational culture, stakeholder relationships, and societal norms. By adopting this holistic view, boards can better anticipate and mitigate potential risks while maximizing the collective benefits of AI adoption. This approach aligns with the growing recognition that AI systems should be designed not just for organizational efficiency but also for the betterment of the company's ecosystem and society as a whole.

The AI Talent Pyramid

To harness AI's full potential, company leaders should focus on developing a comprehensive AI talent strategy. This approach should aim to elevate human intelligence and capabilities across the organization, ensuring that the company remains competitive in an AI-driven landscape. For example, Infosys's three-tiered competence framework consists of the following types of employees:

1. AI-aware workers. Ensure all employees have a basic understanding of AI tools for effective collaboration and cocreation.
2. AI builders. Develop a cadre of professionals who can leverage AI skills to create AI-embedded or AI-reimagined solutions.
3. AI masters. Nurture experts who can design models and innovative methods that work at scale, reducing costs and adding value to the business.

By adopting this approach, organizations can create a workforce equipped to collaborate effectively with AI at various levels of sophistication. This strategy aligns with the World Economic Forum's estimate in The Future of Jobs Report 2020 that 50 percent of all employees will need reskilling by 2025 as technology integration in the workplace increases.

AI as the Great Accelerator in Research

In today's data-driven business environment, AI's role as a powerful accelerator in data processing and decision-making is becoming increasingly crucial. Board members should recognize that AI-based technologies enable their organizations to navigate vast data landscapes at unprecedented speeds. This capability allows for rapid insight generation and more informed strategic decision-making.

AI's impact is particularly valuable in research-intensive fields, such as energy and pharmaceuticals. In these areas, AI is overcoming physical limitations and accelerating progress in critical domains. For instance, AI has been instrumental in expediting carbon capture, utilization, and sequestration (CCUS) experiments in energy research. The vast scale and complexity of soil-based carbon sequestration make it impossible to study comprehensively without AI assistance. In fact, there simply isn't enough accessible soil on Earth to conduct comprehensive CCUS experiments without AI's aid to overcome physical restraints. 

In the pharmaceutical industry, AI is revolutionizing drug discovery. It dramatically reduces the time and cost associated with developing new medications. This enables researchers to overcome the physical limitations of traditional lab-based experimentation. By leveraging AI, pharmaceutical companies can explore a much wider range of potential drug candidates in a fraction of the time it would take using conventional methods.

To operationalize AI as a great accelerator, board members should focus on three key areas: the implementation of a robust digital core and comprehensive data strategy to support accelerated decision-making processes; a strong data governance framework that ensures data quality, accessibility, and compliance and enables the creation of reliable AI models and insights essential to board-level strategic decisions; and the seamless integration of AI technologies into existing systems, facilitating continuous model evaluation, retraining, and effective lifecycle management of AI models.

Economic Impact and Job Market Shifts

According to PwC’s Sizing the Prize: What’s the Real Value of AI for Your Business and How Can You Capitalise?, AI is projected to contribute $15.7 trillion to the global economy by 2030, and boards should position their organizations to capitalize on this growth by developing strategies to leverage AI for increased productivity and new revenue streams. However, this transformation also brings challenges as the rapidly changing nature of work across industries creates a mismatch between existing skills and emerging job requirements. IMF estimates that 40 percent of global employment is already exposed to AI in their article “AI Will Transform the Global Economy. Let’s Make Sure It Benefits Humanity.” To prevent against exacerbating existing inequalities, boards need the right expertise and should prioritize education on AI and its implications to ensure that the workforce can adapt to and benefit from AI-driven economic growth.. While there's no universal approach to navigating the AI revolution, maintaining heightened awareness of its potential impacts is crucial. By proactively addressing these critical areas, boards can help their organizations capitalize on AI's opportunities while mitigating associated risks and ethical concerns. The key is to foster a culture of responsible innovation that aligns with the company's values and long-term strategic goals. 

Addressing Concerns and Ethical Considerations

While the potential benefits of AI are substantial, concerns about job displacement, privacy, and the ethical use of AI persist in enterprise contexts. Deep Instinct’s Voice of SecOps report found that 85 percent of cybersecurity leaders reported an increase in AI-driven cyberattacks, highlighting the growing risks associated with AI implementation. Additionally, algorithmic bias in AI systems has led to discriminatory hiring practices and unequal access to resources in some organizations.

Addressing these concerns requires robust policy frameworks, ethical guidelines, and ongoing stakeholder engagement. To navigate these challenges, boards should consider establishing a dedicated responsible AI office as a central hub for overseeing AI-related activities. This cross-functional team, comprising representatives from the business, software engineering, legal, compliance, information technology, data security, privacy, and risk management teams, would ensure regulatory compliance, foster responsible AI practices, and enhance transparency and accountability in AI decision-making. By implementing a comprehensive governance structure, organizations can effectively mitigate AI-related risks, promote fairness, and build trust with employees, customers, and partners.

The Road Ahead

As AI continues to evolve, its role as a human amplifier is likely to expand. The future of work is not a zero-sum game between humans and machines but rather entails a synergistic relationship in which AI amplifies human potential. As this symbiosis deepens, organizations may find that the true power of AI lies in elevating human intelligence to new heights, not in replacing it.

However, realizing this potential requires careful navigation of the challenges ahead, including reskilling the workforce, addressing ethical concerns, and ensuring that the benefits of AI are distributed equitably across society.

Infosys is a NACD partner, providing directors with critical and timely information, and perspectives. Infosys is a financial supporter of the NACD.

Rajeshwari Ganesan is Infosys's distinguished technologist and a global leader in artificial intelligence and machine learning.