Do You Fear Missing the AI Train?

AI is rapidly emerging as the next transformative technology—comparable to innovations like the steam engine, personal computer, or the internet. Billions have been invested, expectations are soaring, yet a clear and definitive breakthrough remains elusive. As CEOs, CIOs, or CTOs, how can you position your company to leverage AI effectively without falling into the trap of costly, premature investments?

Why AI Feels Familiar to CEOs

The current state of AI is reminiscent of the personal computing revolution of the 1980s. Computers were becoming increasingly powerful, yet practical software was scarce. Companies faced a similar dilemma: invest heavily in proprietary software or wait to adopt the best solutions the market eventually provides. History suggests that unless your company intends to become a technology provider, internally developed solutions rarely match the efficiency, quality, or cost-effectiveness of market-driven innovations.

Should You Wait or Jump In Immediately?

Deciding whether to act immediately or wait until AI’s value proposition becomes clearer depends greatly on your company’s core business and technological orientation.

AI Strategy for Technology Companies

For tech-driven companies whose core product is digital, leveraging AI is imperative—not optional. These companies must continually experiment and pivot to stay competitive; AI is another critical dimension they must consider. Strong internal IT departments and existing software capabilities position them ideally to benefit immediately from AI.

Examples include:

• Github Copilot or Cursor.so: These tools significantly accelerate software development by suggesting code and streamlining the coding process, enabling teams to deliver more using fewer developers. Industry studies (e.g. one from GitHub or another one done by several organizations) suggests productivity increases ranging from 25% to 50% alongside a 50% reduction in web searches by developers. Actual productivity gains depend on specific implementations, developer experience, and organizational readiness.
• Customer Hotline/Support: AI-powered support systems, such as AI whisperers or fully automated responses for common questions, can reduce customer support costs by up to 30%. AI chatbots can handle approximately 80% of routine queries, freeing human resources for more complex tasks. An interesting article can be found for example here.
• Process Automation: Tools like n8n, LogicApps, or Make seamlessly integrate with AI providers (e.g., OpenAI, Google) to inject intelligence into processes beyond traditional algorithmic capabilities. Extending the possibility of  automation for some types of tasks previously requiring human judgment.
• AI Agents: AI agents automate tasks such as calendar management, code reviews, and DevOps tasks, significantly improving everyday productivity.

AI Strategy for Non-Tech Companies

Non-tech companies must carefully evaluate their industry's vulnerability to disruption from AI. Some industries, notably call centers, already face considerable AI-driven pressure and risk a "Kodak moment" if unresponsive. However, for many others, adopting readily available, market-proven AI solutions can provide incremental improvements without substantial risks.

Manufacturers benefit significantly from Machine Learning (ML), improving quality control, enabling predictive maintenance, and optimizing production processes. More powerful and affordable hardware continues to make such solutions increasingly accessible and practical.

Large Language Models (LLMs) also deliver immediate value—for example, by automating and prioritizing customer complaints based on sentiment analysis, urgency, and severity, streamlining human responses.

Practical AI Adoption Examples

Several market-ready AI tools offer immediate business value:

• Microsoft 365 Copilot and Google Workspace Copilot: AI-powered assistance streamlines employee tasks, enhancing productivity and workflow efficiency.
• ChatGPT or Google Gemini: Providing employees with access to these conversational AI platforms increases efficiency and familiarizes your workforce with emerging AI capabilities.
• AI-powered Marketing Tools: AI-driven graphic design and video-editing software increase creativity and efficiency, enabling marketing teams to produce higher-quality content more rapidly.
• Robotic Process Automation (RPA) with AI: RPA platforms such as UiPath automate routine tasks traditionally performed through user interfaces. Integrating AI further expands automation potential by handling processes previously requiring human judgment or intelligence.

ROI from AI investments varies significantly based on specific contexts, implementations, and organizational factors. While these case studies and metrics demonstrate clear potential benefits, success in your company will require thoughtful alignment with your strategic goals, proper change management, and continuous adaptation based on results and market developments.

Conclusion: Balancing Urgency and Caution

AI adoption isn't a one-size-fits-all decision—context and business strategy matter greatly. Tech-driven companies should actively experiment with AI to maintain competitiveness. Non-tech companies can incrementally adopt available AI solutions to boost productivity and employee familiarity. Carefully evaluate your industry’s potential for disruption by AI. Strategic investments, incremental adoption, and staying continuously informed will help your company effectively balance urgency and caution, ensuring you don't miss the AI train.