December 23, 2025 Editor’s Notes:

This is the first of two articles reflecting on the year but Yogi Schulz. Schulz’ long career in IT and experience in industry give him an invaluable perspective on the industry. We are delighted to publish this piece and will look forward to more articles from Schulz and other notable people in the tech industry.

The themes outlined below reflect measurable shifts across the global IT sector in 2025. According to a McKinsey survey, 88 per cent of organizations now use AI in at least one business function. Global IT spending also climbed to over US$5.5 trillion in 2025, a 10 per cent growth from 2024’s numbers. Meanwhile, data-centre activity has hit historic highs, with more than 100 infrastructure deals worth over US$61 billion recorded through November 2025 as companies scramble to build capacity.

Information technology continues to develop rapidly, changing what’s possible. 2025 was no exception. Here are my Top 10 developments. Undoubtedly, there are multiple opportunities to apply these technologies more widely across your enterprise.

1. AI dominated every conversation

In 2025, AI concepts, experimentation with generative AI, and speculation about future adoption and significant impacts have dominated every conversation. Everyone is trying to figure out how AI will impact their organization and their career path.

The rapid adoption of generative AI and the massive investments in AI models and supporting data center infrastructure indicate we’re in the middle of a technology revolution comparable to electricity, the telephone and the Internet.

2. Generative AI is advancing processes and creativity

Incredible investments in improving AI models are producing new models such as Anthropic’s Claude 3.5/3.7, Google’s Gemini 2.5, Microsoft’s Copilot and OpenAI’s GPT-4o and future GPT-5. These AI models are:

• Transforming content, code, research and media creation.
• Improving in sophistication and performance.
• Reducing the frequency of misleading output and hallucinations.

Enterprises are using these AI models not only for automation but also for creative ideation, personalized experiences and advanced analytics across sectors.

3. Massive data center expansion for AI infrastructure

The global boom in generative AI use has driven historic investments in new data center infrastructure. The tech giants and less prominent companies have poured hundreds of billions into new data centers and cloud capacity. These data centers provide capacity for workloads such as AI model development, large-scale inference, large globally distributed applications and real-time data analytics.

New AI applications and new end users are consuming all the long-running improvements in the price-performance of computing technology.

4. U.S. TikTok sale

The U.S. Congress passed a law requiring TikTok owner ByteDance to divest its U.S. operations to non-Chinese ownership. Congress wants to address TikTok’s threat to national security, citing Chinese regulations that require companies to share data, including personal data, with the government upon request. The regulations exemplify authoritarian governments seeking to control the media and influence public opinion. President Trump’s lawsuits against various media organizations indicate an eagerness to suppress media criticism similarly.

As the planned sale has dragged on, it has raised various questions:

• Is it even technically feasible to carve out U.S. end users into a separate computing infrastructure to avoid Chinese regulations without creating a walled garden that would reduce TikTok’s appeal to U.S. end users?
• Could Congress even enforce its law if ByteDance declined to comply? Most U.S. TikTok end users don’t care who owns the platform.

• Can a U.S. President decree who will purchase TikTok’s U.S. operations? Such a decree appears to be a blatant political interference in a business transaction.

The mandated U.S. TikTok sale and other events illustrate that information technology can become entangled in political agendas.

5. AI experimentation

Many enterprises are engaged in AI experimentation and pilots. These AI projects, formally approved or not, are building experience with the requirements and risks of AI application projects.

AI pilots are revealing:

• How poor data quality in enterprise data sources leads to hallucinations that are either funny or dangerous and undermines business value.
• How difficult it is to achieve an appealing business case for AI applications.
• Shortages in IT talent with experience in AI software.

6. Proliferation of IoT and smart devices

The scale of connected Internet of Things (IoT) devices has surged, with billions of endpoints collecting real-time data across homes, enterprises, and cities. The variety of IoT devices has exploded, their capabilities have become smarter, and their unit costs have decreased. The devices have created such an explosion in data volume that AI is needed to analyze it. The related networks and applications power facility operations, predictive maintenance, supply chain optimization and next-generation Smart City applications.

IoT and smart devices underpin a digital transformation that improves performance, reduces costs and increases safety.

7. Low-code/No-code developer platform advances

Professional software developers and end users alike have accelerated application development using low-code and no-code platforms. These platforms have taken the unreasonable pressure to deliver applications off many IS departments.

These platforms democratize software development and reduce time-to-market for internal and customer-facing solutions. Many enterprises are ignoring concerns about the lack of robustness or scalability.

8. Cybersecurity reinvented with AI and quantum-safe tools

Cybersecurity defence remains a top priority for enterprises and governments as threats have become pervasive and increasingly sophisticated. AI-driven defence platforms, zero-trust architectures and early adoption of post-quantum cryptography have proliferated across organizations to protect against automated attacks and future quantum decryption risks.

Cybersecurity defences have increased operating costs for many, while a surprising number of enterprises continue to ignore threats to their finances and reputations.

9. Blockchain beyond cryptocurrency

Blockchain technologies have matured to support secure decentralized ledgers for smart contracts, supply-chain integrity and digital identity management. These applications are expanding the value of blockchain technologies beyond speculative finance into trusted enterprise systems.

Blockchain technologies improve productivity and may yet be adopted in the understandably cautious banking system.

10. Explosion of cloud and edge computing integration

Edge computing has expanded rapidly in 2025, even as cloud computing remains foundational for most enterprises. Edge computing brings data processing closer to where data is generated. Examples include sensors with processing capability in smart factories, autonomous vehicles and municipal infrastructure.

Hybrid and multi-cloud strategies have become the norm as architectures for this integration, improving scalability and resilience while optimizing costs.

Many information technology developments made 2025 an exciting year. Stay tuned for more excitement in 2026.