Reading Insights: The Year in Tech 2025 by Harvard Business Review

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Welcome to my ‘Reading Insights‘ series. Here, is where I share simple takeaways and personal thoughts from articles, papers, and other readings that called my attention.

Together, we’ll explore ideas beyond the “Book Notes” series that help us to improve how we think about management, leadership, and personal growth.

So grab a cup of coffee, and let’s dive into some interesting insights!

And what are we reading today?

Today we will talk about the The Year in Tech 2025 guide by Harvard Business Review.

The Year in Tech, 2025 by Harvard Business Review captures the most recent innovations and challenges driving technology’s role in our work and lives. The guide emphasizes how technology is moving beyond tools to become collaborators in decision-making, creativity, and problem-solving.

The recurring message is clear: success in this new era depends on integrating technology thoughtfully, balancing human insight with machine capabilities, and embracing the cultural shifts that come with it.

A key theme throughout is the need for businesses to adapt rapidly to technological advances without losing sight of ethical considerations and inclusivity.

Whether it’s AI transforming knowledge work, biometrics redefining user authentication, or digital academies closing critical skills gaps, leaders must prioritize responsible innovation. This means aligning tools like generative AI and Web3 with long-term goals, fostering skills for human-machine collaboration, and embedding fairness and sustainability into every decision.

The guide also highlights lessons from industries like construction and electric vehicles, showing that innovation can be incremental but deeply impactful.

Across all examples, the takeaway is that organizations must combine strategic foresight with actionable experimentation.

Whether it’s preparing for an unpredictable AI future or designing systems that empower creators through Web3, the focus should always be on making technology work for people, not the other way around.

What are the key takeaways from The Year in Tech 2025 by Harvard Business Review

Redesign workflows for AI-human collaboration: Identify tasks where AI can augment human decision-making, freeing time for creativity and strategic thinking.

Upskill teams for the future: Create tailored learning programs that address new roles emerging from technologies like generative AI, biometrics, and Web3.

Leverage AI responsibly: Set clear policies for ethical AI use, ensuring transparency, fairness, and the mitigation of risks like bias or data misuse.

Adopt technologies incrementally: Experiment in controlled areas, as seen in China’s EV market, to refine innovations before scaling them broadly.

Empower creators with Web3: Use tools like NFTs and smart contracts to give artists and innovators greater control and more equitable compensation.

Enhance customer engagement through tech: Use spatial computing and biometrics to create immersive, seamless experiences without compromising trust.

Anticipate long-term tech impacts: Apply strategic frameworks like IDEA to prepare for the unpredictable trajectories of emerging technologies.

Promote sustainability in IT: Optimize energy use in data centers, adopt responsible coding practices, and align IT initiatives with environmental goals.

Foster experimentation in your culture: Encourage teams to test and iterate with new technologies, building adaptability and innovation into daily operations.

Focus on people, not just tools: Whether it’s robots in customer service or generative AI in workflows, ensure technology complements human strengths rather than replacing them.

The Human-AI Workplace Has Arrived
by Elisa Farri and Gabriele Rosani

Idea in Brief: AI has moved from being a tool to becoming a partner in the workplace. This transition requires businesses to rethink workflows, upskill teams, and establish ethical practices for effective collaboration.

Summary: The introduction lays out the idea that workplaces are entering a phase where humans and AI collaborate directly. It’s no longer just about automation or efficiency—AI is actively contributing to decision-making and creative processes. To make this shift work, organizations need to redesign workflows and ensure employees are equipped with the skills to work alongside AI effectively.

One point that called my attention is the concept of “fusion workflows.” These are processes where humans and AI share tasks based on their strengths—AI handling data-heavy, repetitive parts, while humans focus on critical thinking and judgment. The challenge is ensuring this partnership is balanced, avoiding over-reliance on AI and addressing potential ethical concerns like bias. Leaders play a key role in setting the direction and ensuring these transitions are smooth and inclusive.

Key Takeaways:

• AI is moving from automation to active collaboration in workplaces.
• Employees need new skills to engage effectively in human-AI workflows.
• Ethical considerations and transparency are critical for trust and fairness.

Robots Are Changing the Face of Customer Service
by Alicia A. Grandey and Kayley Morris

Idea in Brief: Robots are enhancing customer service by handling routine tasks, but their effectiveness depends on thoughtful design and human integration.

Summary: This article explores how robots are being integrated into customer service roles, from concierge bots in hotels to self-service kiosks in retail. The key is finding the right balance—robots should be functional and approachable without trying too hard to mimic humans, which can make interactions feel unnatural and… weird.

One example is giving robots small human-like traits, like a name or a friendly voice, which makes them more relatable. However, robots are not a one-size-fits-all solution. They are best suited for repetitive, predictable tasks, while complex or emotional interactions remain the domain of human workers. For businesses, this means treating robots as part of the team—supporting human employees rather than replacing them outright.

Key Takeaways

• Robots are effective for routine tasks but need to complement human roles, not replace it.
• Relatable design elements, like names or simple emotional cues, improve customer engagement.
• Human workers remain essential for handling complex and emotional customer needs.

Biometrics Are Becoming a Business Reality
by Therese Stowell

Idea in Brief: Biometrics, such as facial and fingerprint recognition, are becoming central to digital customer experiences, balancing security with convenience. Businesses must implement them thoughtfully to address privacy concerns and build trust.

Summary: Biometrics are revolutionizing how businesses enhance customer experiences, particularly in industries like fintech, hospitality, and retail. The article highlights how these technologies simplify identity verification and streamline access to services, from checking into hotels with an app to verifying a car rental without meeting anyone in person. Traditional banks, initially hesitant, followed fintech disruptors like Revolut in adopting biometrics to meet customer demand for seamless, secure services during the pandemic.

Yet, the adoption of biometrics comes with challenges. While they increase convenience, they also introduce ethical questions about data storage, biases in AI systems, and potential misuse. For instance, AI algorithms trained on non-representative data can exclude certain groups, and the storage of biometric data raises privacy concerns. Companies implementing biometrics need to balance the need for innovation with building customer trust, ensuring the technology is inclusive and secure.

Key Takeaways

• Biometrics simplify user authentication, offering a frictionless customer experience.
• Ethical implementation and transparency in data handling are essential to gaining trust.
• AI-powered biometric systems must be developed using diverse datasets to avoid bias.

How Early-Adopter Companies Are Thinking About Apple Vision Pro
by Cathy Hackl

Idea in Brief: The Apple Vision Pro isn’t just a product; it’s a gateway to spatial computing, a field that blends virtual and physical worlds. Early adopters, like Lowe’s and e.l.f. Cosmetics, are leveraging the device to create new customer experiences and business opportunities.

Summary: This article explores how companies are experimenting with the Apple Vision Pro to embrace spatial computing. Lowe’s, for instance, uses it to allow customers to visualize home renovations in immersive 3D spaces, simplifying complex design decisions. Similarly, e.l.f. Cosmetics is engaging with consumers by creating personalized, interactive beauty experiences that go beyond traditional shopping. The PGA Tour is also tapping into this technology by letting fans experience golf courses in 3D, offering immersive insights into the game.

What’s striking is how these companies view spatial computing not just as a novelty but as a way to redefine customer engagement and brand identity. Yet, the challenges are significant: developing apps for the Vision Pro requires specialized skills and significant investment. Companies must weigh the potential of leading a new wave of innovation against the risk of betting on a nascent technology.

Key Takeaways:

• Spatial computing opens up new opportunities for immersive customer experiences.
• Early adopters like Lowe’s and e.l.f. Cosmetics are using the Vision Pro to experiment with innovative ways to engage their audiences.
• Developing for spatial computing requires specialized knowledge and investment, but the rewards include early market leadership and deeper customer loyalty.
• The transition to spatial computing is still experimental, and its long-term business impact remains uncertain.

Three Drivers of China’s Booming Electric Vehicle Market
by Chengyi Lin

Idea in Brief: China dominates the global electric vehicle (EV) market due to its strategic experimentation, operational problem-solving, and deep focus on core battery technology. These moves provide lessons for other industries aiming to scale innovations.

Summary: China’s rise as the leader in EV production, accounting for 60% of global EV sales and producing half the world’s electric cars, is built on three pillars. First, Chinese companies like BYD and Geely started by experimenting in adjacent industries, such as electric buses and motorcycles. This gave them the chance to develop and refine battery technologies before venturing into the larger EV market. For example, BYD leveraged its experience with electric buses to improve battery performance for cars.

Second, they solved operational challenges by working with local entities, such as taxi companies, to refine charging schedules and reduce energy grid strain. By customizing their approach, they addressed issues like limited range and lengthy charging times, making EVs practical in dense urban areas. Third, China doubled down on core battery technology, benefiting from access to critical raw materials like rare earth metals and collaborating extensively with international partners to boost expertise. This comprehensive strategy positioned Chinese automakers to outpace competitors like Tesla in critical markets.

Key Takeaways:

• Experimenting in smaller markets (e.g., buses and motorcycles) provided a testing ground for scalable EV technology.
• Solving real-world operational issues, such as efficient charging, made EV adoption feasible in urban environments.
• Investing heavily in battery development and supply chain control enabled cost reductions and innovation.
• Collaboration with international automakers and tech firms helped strengthen their EV ecosystem.
• For global expansion, Chinese automakers need to replicate this adaptability in Western markets, including addressing local regulations and infrastructure challenges.

AI Is Testing the Limits of Corporate Governance
by Roberto Tallarita

Idea in Brief: The development of AI is outpacing the traditional structures of corporate governance, raising critical questions about balancing profit motives, safety, and social responsibility. The recent tumult at OpenAI mentioned highlights the complexities of governing AI in the public interest.

Summary: This article discussed the challenges of managing AI development within current corporate governance frameworks. Using OpenAI as a case study, it explores the tensions between profit-driven motives and the broader mission of AI safety. For example, OpenAI’s charter prioritizes humanity’s benefit over profits, a contrast to traditional corporate goals. Despite these ideals, the controversy surrounding CEO Sam Altman’s firing and eventual reinstatement exposed weaknesses in governance structures meant to prioritize social good.

The analysis identifies several lessons, including the inability of traditional governance to safeguard the social implications of AI. Even creative approaches, such as public benefit corporations like Anthropic, struggle against the inherent pressures of profit-driven markets. The piece also warns that catastrophic risks associated with AI—such as rogue, uncontrollable systems—require extraordinary governance measures. The solution lies in aligning profit motives with safety goals, while emphasizing diverse perspectives on corporate boards to encourage well-rounded decision-making.

Key Takeaways:

• Traditional governance structures are bad equipped to manage the societal risks coming with AI.
• Companies like OpenAI attempt innovative governance approaches, but market forces still dominate.
• Corporate boards need cognitive diversity to balance expertise and perspectives effectively.
• Aligning profit motives with safety measures can make AI governance more sustainable.

Understanding the Trade-Offs of the Amazon Antitrust Case
by Chiara Farronato, Andrey Fradkin, Andrei Hagiu, and Dionne Lomax

Idea in Brief: Amazon faces antitrust scrutiny for practices like bundling services and prioritizing its own products. The debate raises fundamental questions about balancing innovation, competition, and consumer benefit.

Summary: This article examines the U.S. Federal Trade Commission (FTC) lawsuit against Amazon, highlighting its focus on practices like bundling the Prime badge with its Fulfillment by Amazon (FBA) service and enforcing implicit price parity rules. Critics argue these practices harm competition by limiting sellers’ options and raising costs, which are often passed on to consumers. For example, requiring sellers to use FBA for Prime eligibility could discourage them from exploring alternative fulfillment solutions.

Amazon defends these practices by pointing to the reputational value of the Prime badge and the need to maintain consistent customer experiences. The authors explore the complex trade-offs: while such strategies ensure high standards and convenience for consumers, they also risk consolidating power and limiting marketplace diversity. The article concludes with a discussion on potential remedies, such as behavioral adjustments to promote fairness without dismantling the economies of scale and convenience that benefit consumers and sellers alike.

Key Takeaways

• Price Parity Rules: Implicit enforcement can discourage competitive pricing across platforms.
• Advertising Challenges: Sponsored listings on Amazon may disadvantage smaller sellers and inflate consumer costs.
• Proposed Remedies: Behavioral fixes, such as increased transparency and audits of ranking algorithms, may offer balanced solutions.
• Actionable Insight: Regulators and companies must collaborate to ensure competitive fairness while preserving consumer benefits like convenience and cost savings.

Can the Construction Industry Be Disrupted?
by Mark Erlich

Idea in Brief: Despite being seen as lagging behind in innovation, the construction industry is slowly adopting technologies like Building Information Modeling (BIM) and digital management tools. The shift is evolutionary rather than revolutionary due to the sector’s unique challenges and decentralized structure.

Summary: The construction industry has long been criticized for its resistance to change and lack of technological sophistication, yet progress is evident in areas such as BIM. This digital tool replaces traditional blueprints with 3D models, enabling architects, engineers, and contractors to visualize projects and resolve issues before physical construction begins. Such advancements are helping large firms streamline operations and cut costs, but their adoption is limited to well-capitalized players due to high upfront investments.

Tools like drones and exoskeletons are gaining traction, providing incremental improvements without disrupting workflows entirely. The industry’s fragmented structure and reliance on subcontractors further slow the pace of widespread adoption. However, the shift towards digitization and technology integration signals a future where efficiency and safety may see some gains.

Key Takeaways:

• Firms can enhance coordination and reduce costs by incorporating Building Information Modeling (BIM) into their workflows.
• Incremental Tech Adoption: Instead of waiting for robotics to revolutionize the sector, focus on smaller innovations like drones or digital management systems to improve efficiency.
• Invest Strategically: Larger firms should lead in adopting high-cost innovations, with an eye on long-term returns.
• Train the Workforce: Introduce tech skills into training programs to prepare workers for a digitally enabled future.
• Plan for Gradual Change: Embrace an evolutionary mindset; major disruptions are unlikely in the near term.

What Is Responsible Computing?
by Rashik Parmar, Marc Peters, and Llewellyn D.W. Thomas

Idea in Brief: Responsible computing integrates environmental, social, and ethical principles into IT systems. By addressing areas like energy efficiency, data privacy, and sustainable design, organizations can align technology with global sustainability goals.

Summary: This article introduces a systemic framework for responsible computing, developed by IBM, that tackles interconnected challenges such as environmental impact, ethical data use, and inclusivity in IT. The framework is built on six pillars: data centers, infrastructure, code, data, systems, and impact. Each pillar emphasizes metrics like energy consumption, greenhouse gas emissions, and ethical decision-making to guide organizations toward sustainability.

For instance, data centers consume vast amounts of energy, yet many operate at a fraction of their potential efficiency. Leaders are encouraged to evaluate their energy sources and explore renewable options. Similarly, responsible code is presented as a way to reduce computational overhead, with KPIs like function-point efficiency and carbon footprint per software process. These efforts align with broader goals such as the United Nations’ Sustainability Development Goals (SDGs), encouraging organizations to see IT not just as a cost center but as a driver of positive social and environmental change.

Key Takeaways:

• Optimize energy use: Monitor data center efficiency, focusing on cooling systems and renewable energy adoption.
• Promote ethical IT: Develop systems with fairness, transparency, and accountability to reduce biases and build trust.
• Enhance coding practices: Train developers in sustainable coding principles to lower computational waste and energy costs.
• Align with SDGs: Evaluate the social and environmental impacts of IT projects to contribute meaningfully to global goals.
• Involve all stakeholders: Ensure the entire organization, from IT to finance, supports the shift to responsible computing.

Generative AI and the Transformation of Knowledge Work
by Maryam Alavi and George Westerman

Idea in Brief: Generative AI is reshaping knowledge work by automating structured tasks and enhancing human cognitive capabilities. The key to leveraging its potential lies in how individuals and organizations integrate these tools into their workflows.

Summary: This article discusses the profound implications of generative AI for knowledge work, which spans both structured tasks, like payroll processing, and unstructured tasks, such as creative problem-solving. Generative AI, with its ability to perform complex cognitive functions, is redefining the boundaries of what machines can do. By automating repetitive elements of work, these tools free up mental capacity for higher-value, unstructured tasks. For example, lawyers at Allen & Overy use AI to draft contracts, enabling them to focus on nuanced legal analysis.

The authors emphasize that while AI offers significant benefits, its adoption must be intentional. Beyond reducing cognitive load, generative AI can support critical thinking, creativity, and knowledge sharing. Tools like Duolingo’s AI-powered role-play feature illustrate how generative AI can deliver personalized feedback and accelerate learning. For organizations, fostering a culture of experimentation and implementing clear policies around AI use are critical to reaping its benefits responsibly.

Key Takeaways:

• Use generative AI to automate routine tasks, saving time for strategic and creative work.
• Leverage AI tools to enhance problem-solving by generating diverse ideas and connecting unexpected concepts.
• Train employees to use AI as a mentor or coach, offering personalized learning and feedback.
• Set clear guidelines to address potential risks, such as biased decisions or data privacy breaches.
• Encourage team-wide sharing of AI innovations to build collective intelligence and drive responsible adoption.

Web3 Could Change the Business Model of Creative Work
by Alex Tapscott

Idea in Brief: Web3 introduces a “read-write-own” model for the internet, empowering creators to manage, monetize, and distribute their work independently. This transformation could reduce the reliance on traditional gatekeepers and open new opportunities for wealth creation in the creative industries.

Summary: The article explores how Web3 technologies can reshape the creative economy, shifting power from large platforms back to creators. Unlike Web1 and Web2, where creators often lose control of their intellectual property (IP), Web3 offers tools like smart contracts and non-fungible tokens (NFTs) that allow creators to monetize their work transparently. These technologies enable automatic royalty payments and IP tracking across platforms, ensuring artists get fair compensation even as their work circulates globally.

For instance, the startup MV3 leverages NFTs to involve fans directly in the creative process of building characters and narratives. This model empowers fans to become co-creators, fostering a collaborative community while simultaneously funding new creative ventures. Additionally, innovations like OTOY’s OctaneRender utilize blockchain to manage IP rights for lifelike digital renderings, democratizing access to high-quality graphics production. These examples highlight the potential of Web3 to disrupt traditional entertainment and art industries, paving the way for fairer, more inclusive business models.

Key Takeaways:

• Implement smart contracts to ensure artists receive fair compensation whenever their work is used or resold.
• Use NFTs to directly involve audiences in funding and co-creating new projects, strengthening community engagement.
• Explore Web3 platforms to bypass traditional gatekeepers, allowing creators to maintain greater control over their IP and earnings.
• Leverage blockchain for transparent tracking of creative assets, which can enhance trust and simplify revenue-sharing agreements.
• Build sustainable creator communities by aligning financial incentives with collaborative governance structures.

Using “Digital Academies” to Close the Skills Gap
by Rubén Mancha and Salvatore Parise

Idea in Brief: Digital academies are powerful tools for closing the skills gap in organizations, combining experiential learning, peer collaboration, and tailored training. They address critical challenges in upskilling employees while fostering cultural and digital transformation.

Summary: This article explores how digital academies can transform an organization’s ability to upskill employees in data science and digital technologies. Unlike generic online courses, these academies are deeply embedded in an organization’s culture, focusing on experiential learning and aligning with its strategic goals. By designing courses for varied employee segments—like citizen data scientists and translators—companies can meet specific needs while fostering collaboration and innovation.

A standout example is DuPont’s Spark Digital Academy, which launched in 2021. This initiative created a culture of data and agility across the organization, offering foundational and advanced courses on topics like robotic process automation and data science. Employees applied what they learned directly to projects, improving processes and developing digital products. The academy’s focus on flexibility and real-world application made it a success, with over 500 participants driving the organization’s broader transformation.

Key Takeaways:

• Design programs that cater to diverse roles, from frontline employees to leadership, ensuring that training is relevant and actionable.
• Incorporate hands-on projects into training to reinforce learning and demonstrate immediate business value.
• Build a support system for alumni through peer networks, mentoring, and continuous learning pathways.
• Partner with external experts when resources are limited, accelerating the development of scalable training programs.
• Use flexible course formats—like on-demand and hybrid models—to accommodate different learning preferences and work environments.

How to Prepare for a Gen AI Future You Can’t Predict
by Amy Webb

Idea in Brief: Generative AI is advancing rapidly, but predicting its full impact is challenging. Organizations must focus on preparing for uncertainties by building flexible strategies, emphasizing collaboration between humans and AI.

Summary: This article underscores the importance of embracing the uncertainty surrounding generative AI’s future. Webb argues that leaders often overestimate AI’s short-term potential while underestimating its broader, long-term implications. She highlights past cycles of AI enthusiasm followed by disillusionment, urging organizations to temper their expectations. Generative AI is not a monolithic solution; it requires integration into workflows, human oversight, and ongoing evaluation to manage risks like bias and compliance issues.

Webb introduces the IDEA framework—Identify, Determine, Extrapolate, and Anticipate—as a strategic tool for navigating AI’s evolution. Leaders should align AI initiatives with organizational strategy while remaining adaptable. For example, rather than replacing workers, businesses can use generative AI to complement human skills, enhancing innovation and productivity. By fostering a culture of continuous learning and foresight, organizations can stay ahead of technological disruption and create value through human-AI collaboration.

Key Takeaways:

• Develop flexible strategies that prioritize adaptability over rigid, long-term predictions.
• Use the IDEA framework to align AI integration with business strategy while anticipating risks and opportunities.
• Focus on collaboration between humans and AI by upskilling employees in areas like delegation and critical thinking.
• Implement continuous evaluation processes to monitor AI tools for compliance, accuracy, and ethical considerations.
• Avoid rushing to cut costs with AI; instead, leverage its potential to create new business models and revenue streams.
• Encourage a culture of experimentation and learning to harness generative AI’s strengths responsibly.

The Year in Tech, 2025 is a fascinating look at how technology is changing the way we work and live.

It’s a great reminder that the real power of technology comes from how it helps us solve problems, connect, and create something better together.

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