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11 minute read
Don’t Overlook How AI’s Impact Reaches Beyond Technology
Once considered abstract, AI is now evolving into a transformative force that will shape every business. For executives outside the tech space, AI might seem like a distant innovation—intriguing but not essential to today’s business priorities. Yet with AI’s accelerating impact, every executive will soon need to understand its implications for their strategy, operations, and competitive edge. This is a future that will require every executive to adapt, regardless of industry.
This article doesn’t dive into specific AI applications for individual industries. Instead, it provides three crucial insights every executive should know as they prepare for AI’s impact. While these ideas may feel forward-looking, AI’s fast pace suggests they could become central business priorities sooner than anticipated.
Each of the following sections offers a distinct view of AI’s future:
- AI-Driven User Interactions – How advancements in AI will change the way people interact with workspaces and technology.
- Foundational Growth Challenges – The critical infrastructure challenges that will shape AI’s scalability and future impact.
- Global Influence – AI’s emerging role as a strategic asset in global relations and the influence of policy on AI’s direction.
Together, these insights provide a foundation for understanding AI’s role in the future, helping executives consider its strategic potential before it becomes a daily reality.
Insight #1: AI-Driven User Interactions – A New Era of Workplace Experience
As AI evolves, it’s transforming how we interact with both digital and physical spaces, ushering in a new era of user experience in the workplace. Advances in visual intelligence and spatial computing—technologies that blend digital information with our physical surroundings—are making workspaces more adaptive, responsive, and interactive.
The Power of Visual Intelligence
At the forefront of this shift is the concept of visual intelligence, which uses AI to interpret visual data in real time and respond contextually to user actions. With extensive experience in developing user-focused technology at Apple, Mike Rockwell, Apple’s Vice President of the Vision Products Group, has led his team in developing the Vision Pro—a device combining high-resolution visuals with spatial computing to redefine how users interact with digital information in physical spaces. As Rockwell described it, Vision Pro is “an infinite canvas that brings the digital world into your physical space,” allowing users to engage with information intuitively, without the confines of traditional screens.
Imagine walking into a meeting room that recognizes who you are and adjusts the environment to support your objectives. Documents, project notes, or relevant data visualizations could appear on walls or other surfaces around you, projected directly into your view without the need for physical screens. This setup not only enhances functionality but represents a more human-centered approach to AI by aligning technology with natural behaviors. The AI adapts to the user’s needs in real time, reducing friction in digital interactions and allowing focus to remain on critical tasks.
Research from Harvard Business Review provides further context, showing how augmented reality (AR) technology, which integrates digital data with physical environments, is already helping organizations enhance productivity and worker performance. AR allows users to interact with their environment in a way that feels natural and effective, a fundamental goal of visual intelligence and spatial computing. AI-driven, immersive workspaces allow businesses to create environments that facilitate skilled, efficient work, emphasizing both employee engagement and performance.
Immersive Workflows and Context Awareness
But visual intelligence is only one part of the AI revolution in user experience. When combined with spatial computing, the possibilities multiply. Spatial computing allows environments to interpret gestures, eye movements, and other subtle cues, further personalizing and adapting to each user’s needs. Rockwell highlighted the potential for these environments, noting that the Vision Pro “blends the physical and digital into one experience,” which makes collaboration and decision-making feel more organic and less reliant on traditional interfaces.
Imagine entering a workspace where, with a simple gesture, a 3D representation of a project appears for everyone to interact with. AI-driven environments become “smart” by anticipating user intent, presenting relevant information, and adjusting tools based on situational context. This kind of context-aware AI creates a workspace that feels like an extension of the user, enhancing engagement and allowing teams to work together in a more cohesive and intuitive way. A study published in the Journal of Artificial Intelligence Research further supports this, suggesting that AI-driven, adaptive interfaces improve efficiency by learning and adjusting to user behaviors, ultimately creating more intuitive interactions.
What This Means for the Workplace of Tomorrow
The implications for executives and the workplaces they provide to their employees can be significant. AI-driven interactions and adaptive workspaces represent a move toward environments that foster focus, collaboration, and effectiveness. Rather than relying on standalone software or complex interfaces, executives can now consider how AI-powered, human-centered environments might reshape their organization’s approach to work, unlocking new levels of engagement and productivity.
Insight #2: Foundational Growth Challenges – Navigating AI's Infrastructure and Sustainability Hurdles
As AI continues to advance, its integration across industries reveals significant infrastructure and sustainability challenges. These foundational issues will play a defining role in AI’s future, determining how far and how sustainably AI can scale. For Alexandr Wang, CEO of Scale AI and one of Silicon Valley’s youngest billionaires, addressing these challenges is critical for AI’s responsible growth. As Wang pointed out in his WebexOne interview, “the infrastructure to support AI at scale is still in its infancy,” underscoring that AI is only beginning to realize its transformative potential.
Data Limitations – The End of Public Data and the Rise of Frontier Data
One of the most immediate challenges facing AI is a data bottleneck. Publicly available data, which has powered AI’s growth so far, is reaching its limits. Wang explained that “we’ve exhausted much of the readily available public data,” meaning that AI systems are running out of new, valuable information to process. Without access to new data, AI’s capabilities will advance only as far as the data it’s fed.
To address this data ceiling, Wang pointed to two emerging solutions:
- Frontier Data: This involves obtaining new, unique datasets that go beyond what’s available publicly. Frontier data can come from proprietary sources or highly specific areas not covered in traditional datasets, offering a more tailored and higher-quality source of information. Accessing this data can unlock AI’s potential in domains that require specialized knowledge or real-time updates, like healthcare diagnostics or financial forecasting.
- Private Data: Another solution lies in private or enterprise data that is securely sourced from within organizations. This type of data is particularly valuable because it is often highly specific and context-rich, enabling AI to deliver insights that are directly relevant to the business’s operations. However, working with private data raises critical ethical and privacy considerations, making responsible data management and compliance a top priority for any organization pursuing this route.
As Wang noted in an interview, “better data results in better AI.” Organizations that invest in quality data sources, whether frontier or private, position themselves to derive more accurate, meaningful insights from their AI systems.
Energy Consumption – The Double-Edged Sword of Powering AI
Energy consumption presents a second, major challenge. AI models, especially large-scale models like language models and deep neural networks, demand enormous computational resources, translating into substantial power requirements. Wang noted that, at the current pace, AI could soon require up to 20 gigawatts of power—an amount comparable to the energy needs of several large cities. Beyond financial costs, AI’s energy demands carry significant environmental implications, particularly as companies consider sustainability goals.
A report from MIT Technology Review underscores this dilemma, noting that “AI is an energy hog.” Current projections suggest that electricity consumption from AI and other high-power applications could double in the coming years, potentially adding the energy equivalent of a new country to the global demand. For executives who are also focused on climate responsibility, this challenge presents a difficult choice: scale AI operations to improve business performance, or limit AI’s growth to reduce environmental impact.
In response, some AI leaders are exploring alternative energy solutions, such as nuclear power, to offset AI’s energy footprint. However, Wang and others recognize that adopting large-scale energy solutions may still not fully reconcile AI’s rapid growth with environmental sustainability. Some companies are looking at ways to optimize algorithms and create more energy-efficient models to reduce power needs while maintaining high performance. For executives, the reality may be that the benefits of scaling AI will come with trade-offs, particularly when balancing sustainability goals with operational growth.
Compute and Hardware Constraints – Scaling AI with a Resilient Infrastructure
As AI becomes more integral to business operations, the need for high-performance computing hardware grows, particularly in the form of advanced processing chips designed specifically for AI tasks. However, the production of these chips is highly concentrated geographically, with a significant portion manufactured in Taiwan. This concentration creates a supply chain vulnerability, as geopolitical tensions or disruptions in this region could threaten the supply of critical components, halting AI’s progress for many companies reliant on these specialized chips.
Addressing this challenge requires investing in more diversified production and exploring innovations in chip design that make AI hardware both resilient and efficient. Companies are also turning to cloud infrastructure and distributed computing, which can decentralize processing and reduce dependency on any one supplier or region. This approach enables scalable, flexible solutions to support AI workloads, particularly for companies that may lack the resources to build and maintain in-house infrastructure.
Agentic AI – Toward Autonomous Systems
A major future direction Wang emphasized is agentic AI—AI systems that can operate independently and autonomously handle complex workflows. Rather than performing isolated tasks, agentic AI systems can act as "agents" within an organization, capable of executing multi-step processes, making decisions, and adapting to evolving conditions with minimal human input. In this way, agentic AI could be a leap forward from current AI capabilities—creating a system that operates more like a collaborative partner than a static tool.
For example, agentic AI could be applied in sectors like customer service, where AI agents could independently resolve queries across multiple platforms, or in supply chain management, where AI could adaptively respond to disruptions or shifts in demand. However, agentic AI requires a strong foundation of high-quality data, reliable infrastructure, and substantial computational power, making it essential to address the challenges outlined above to enable this next-generation AI capability.
Preparing Your Business for AI’s Foundational Challenges
Understanding these foundational growth challenges is essential for executives as they consider how AI will fit into their organization’s strategy. By addressing data limitations through frontier and private data, meeting energy needs sustainably, ensuring resilient compute infrastructure, and preparing for the rise of agentic AI, businesses can develop a strong, sustainable foundation for AI innovation. Taking proactive steps in these areas will position organizations to harness AI’s transformative power responsibly and effectively.
Insight #3: The Global Ripple Effect – AI's Far-Reaching Implications
Though your business may operate domestically, the global influence of AI technologies is inescapable. Implementing AI not only transforms individual businesses but also influences international trade, labor markets, and political stability, creating a ripple effect with consequences for global economics and governance. As Fareed Zakaria, host of Fareed Zakaria GPS on CNN and a renowned foreign affairs expert, stated during his WebexOne keynote, “AI is not just a tool; it’s a force reshaping global economics and politics.”
The Economic Shift: AI as a Global Economic Driver
AI has the potential to be one of the most transformative forces in the global economy since the Industrial Revolution. A report by the McKinsey Global Institute projects that AI could add up to $13 trillion to the global economy by 2030, which would increase global GDP by about 1.2% annually. This growth potential makes AI adoption not just a strategic advantage but also a catalyst that could redefine the competitive landscape for nations and companies alike, this economic shift is likely to be uneven, leading to disparities between countries that effectively harness AI and those that lag. Zakaria warned that AI could widen global inequalities as countries with advanced technology infrastructures and resources stand to benefit disproportionately, while those without access to these resources risk being left behind. “Nations that lead in AI will dominate economically and politically,” he explained, pointing to an emerging “AI divide” reminiscent of the digital divide that characterized the early internet era.
Global Insight: For executives, this economic divide poses both opportunities and ethical considerations. Companies operating in AI-advanced countries have a competitive edge, but they must also consider how their innovations could affect global stability. Engaging in collaborative, cross-border AI partnerships can help mitigate some of these inequalities, creating a more inclusive economic impact.
Geopolitical Tensions and AI’s Role as a Strategic Asset
AI’s impact extends beyond economics into geopolitics, reshaping power structures and heightening competition among global superpowers. Zakaria highlighted the “AI arms race” between the United States and China, where both nations are investing heavily in AI, viewing it as a critical component of national security and technological dominance. As Zakaria warns, AI now occupies a place in geopolitics that rivals the role of nuclear technology in the 20th century.
In a recent report, the Brookings Institution highlighted that China alone has committed hundreds of billions of dollars to become the world leader in AI by 2030. This competition between the U.S. and China is already influencing global trade policies, intellectual property laws, and alliances. Zakaria emphasized that “AI will increasingly be used as a tool of influence, and nations will wield it to project power, much like they did with military and nuclear capabilities in past eras.”
For businesses, this geopolitical climate means that AI-related decisions may have implications beyond their immediate goals. Companies engaged in AI innovation should stay informed about international AI regulations and understand how geopolitical dynamics could impact supply chains, data governance, and cross-border operations.
AI and National Politics: The 2024 U.S. Election and Beyond
Another significant point Zakaria raised was AI’s impact on domestic politics, particularly in the United States. He expressed concern over AI-driven misinformation campaigns and their potential to undermine democratic processes, stating, “AI has the power to influence public opinion, and when used irresponsibly, it could erode trust in democracy itself.” In the lead-up to the 2024 presidential election, there is growing worry that AI-generated deepfakes, fake news, and targeted misinformation could distort public opinion and challenge the integrity of electoral systems.
According to a Pew Research Center survey, 56% of Americans are concerned about AI’s potential influence on elections, particularly as it relates to misinformation and voter manipulation, underscores the need for policies that safeguard democratic systems from AI misuse. Zakaria suggested that within the next four years, the U.S. will need to develop comprehensive regulations for AI in media, protecting the public from disinformation while allowing space for beneficial AI applications in government and civic engagement.
For executives, the rise of AI-driven misinformation is a reminder of AI’s dual nature: while it can empower businesses and improve efficiencies, it also has a dark side that requires careful oversight and ethical consideration. Businesses must adopt responsible AI practices and support transparency and ethical standards in AI deployment to mitigate risks that could affect public trust and social stability.
Global Responsibilities: Ethical AI and the Ripple Effect
Executives considering AI implementation should recognize that their decisions contribute to a larger, interconnected impact. Zakaria urged leaders to view AI through a global lens, where ethical considerations are as important as competitive advantages. He emphasized the responsibility businesses hold to use AI in ways that align with principles of fairness, transparency, and sustainability. “If AI is going to be the defining technology of this era, then it is incumbent upon those who wield it to consider the long-term consequences,” Zakaria stated.
In an increasingly interconnected world, AI implementation can have unforeseen ripple effects across borders and industries. For example, an AI innovation that displaces jobs in one region may result in economic challenges elsewhere. Ethical frameworks for AI development, along with policies that promote global cooperation, are essential to ensure that AI serves as a positive force in international development.
Your Role: Act Responsibly, Think Globally
For executives, the insights offered by Fareed Zakaria serve as a powerful reminder of AI’s reach and the responsibilities it entails. Implementing AI is not a neutral act; it can influence global stability, economics, and governance. By considering the broader ripple effects of their AI strategies, companies can act as responsible stewards of this transformative technology, balancing competitive goals with a commitment to ethical and sustainable practices.
From Insight to Action: Preparing Your Business for AI
AI is no longer a distant technology reserved for Silicon Valley or high-tech industries; it’s a transformative force already impacting diverse fields and redefining the landscape of work, decision-making, and strategy. For many executives outside of the technology sector, understanding AI’s role in their business can seem daunting. Yet, the insights gathered here make clear that, while the path to AI integration presents complex challenges, it also offers substantial rewards for those who approach it with forethought and purpose.
The three areas discussed—AI-driven user interactions, foundational growth challenges, and global impact—reveal that AI is reshaping the future of business in profound ways. With immersive, context-aware workspaces, AI-driven interactions are set to redefine workplace experiences, while emerging energy and infrastructure challenges present both obstacles and innovation opportunities. AI’s global impact highlights that, regardless of where your industry operates, adopting AI has ripple effects across economies and political systems, underscoring a growing responsibility for ethical AI deployment.
As executives look to incorporate AI responsibly, several key considerations come to light:
- Invest in Data Strategy and Security: Reliable, high-quality data is the bedrock of effective AI. Executives should prioritize collecting, managing, and securing proprietary or frontier data that aligns with their specific business needs. This includes setting ethical guidelines for data use and protecting private information to maintain public trust.
- Evaluate and Plan for Energy Requirements: AI’s power demands are substantial and growing. Companies committed to sustainability may need to balance their AI ambitions with energy-efficient practices, investing in more optimized AI models or exploring renewable energy sources. Now is the time to build infrastructure plans that can support both AI scalability and corporate sustainability goals.
- Consider AI’s Broader Impact on Society and the Workforce: AI is more than a productivity tool; it has implications for workforce transformation and the ethical use of technology. Executives should develop a clear stance on AI ethics and prepare their organizations for the social changes AI may bring. This might include workforce reskilling, establishing guidelines for ethical AI, and collaborating with industry partners to support responsible AI adoption.
- Stay Informed About Policy and Regulatory Changes: AI is increasingly central to global policy discussions. Keeping abreast of emerging regulations and being proactive in understanding how these may impact your industry will help companies navigate potential risks and remain competitive.
Here’s the takeaway in a nutshell: AI presents not just a strategic advantage but also a responsibility. By thoughtfully addressing the technical, ethical, and operational facets of AI, executives can harness AI to drive innovation and sustainable growth. The future of AI is already here, and the actions taken today will define how it shapes our organizations, industries, and global society in the years to come.
