The hidden tax of complexity and speed

The hidden tax of complexity and speed leaves a lasting impact on businesses. Every new process, tool, and approval layer carries a cost that often goes unnoticed on a balance sheet. Nearly 58% of professionals spend at least three hours weekly on administrative tasks, and over half find this side of work frustrating. As teams become increasingly busy, too much effort is absorbed by the machinery surrounding their work.

Complexity can slow decision-making and make it more fragile. Speed, however, switches off critical thinking and pushes individuals to make decisions hastily in order to avoid stress. While AI has made execution faster, it has not necessarily meaningfully improved decision quality across the board or consistently. For businesses to make the most gains from their tech choices, they must thoroughly reevaluate their processes and training.

Basic AI use, particularly generative AI, is not going to meaningfully grow the business compared to those who take more care in tailoring it. However, this is easier said than done, as cognitive aspects of work are often overlooked and may simply be ticked off without proper evaluation. Keeping process improvement a focused aim and ensuring it evolves alongside new technologies like AI, while also addressing essential human requirements such as fulfillment, agency, and flow, is not easy.

Nevertheless, getting it right will separate high performers from average thinkers. The journey begins with small steps, as the ancient wisdom "a journey of a thousand miles begins with a single step" echoes across various philosophies, cognitive behavioral therapy, and practical guides to business. To avoid drifting away from best practices and organizational goals, regularly review various departmental lenses and priorities aligned with industry, policies, customer contracts, and tech stacks.

Regularly revisiting workflows to identify areas for streamlining and ensuring the purpose and context of the process aren't hidden from those responsible for completion is crucial. Focus on priorities, aiming to do less, better, while using AI tools to uplift performance. Consolidating information and reducing tool switching are fundamental tasks that many consultancies specialize in.

A Chief Operating Officer (COO) is well positioned to collaborate with the Chief Information Officer (CIO) to ensure any data usage changes are implemented smartly, without shadow AI or ad hoc workarounds that could hinder collective efforts. AI should be treated as an assistant, not a replacement. While AI's potential is promising, costs and performance are variable, and smart users are crucial for maximizing its benefits.

Training on model use, prompt engineering, custom GPTs, and skills is essential for employees to harness the full potential of AI. However, AI can always fail due to power cuts, API failures, or dependency removals. Therefore, people must not solely rely on AI for their jobs. The hidden costs of these invisible, cultural 'soft' aspects of work are often neglected, yet they can mount up.

These costs encompass more than financial outgoings and risks, including time mismanagement and opportunity costs. To control costs, improve service, and enhance employee experience, businesses must stay on top of dependencies, sprawl, shadow IT, evolving models, agentic drift, and token costs. Leaders must also research and experiment with operations, increasingly adopting a consultant mindset within their own businesses.

Ultimately, investing in human intelligence is paramount. Training should focus on developing IT skills, systems thinking skills, the engineering mindset, and soft skills that hold organizations together. Employees need to develop critical thinking skills to validate, evaluate, and properly act on AI outputs. Blindly trusting AI output is counterproductive.

Awareness and mindfulness are key to ensuring leaders continually check and tweak their processes to adapt to the winds of technology and the economy.