AI Works Best When It Strengthens Human Capability

AI and sensemaking

Sensemaking is the process of gathering information, interpreting it, understanding its significance and deciding what actions may be appropriate. It is how we turn information into understanding.

Perhaps the greatest initial use of Large Language Models (LLMs) such as ChatGPT was helping people make sense of information faster than they could on their own. Users quickly discovered that AI could summarize lengthy reports, explain unfamiliar concepts, simplify technical language, compare alternatives, identify missing considerations and provide additional perspectives for evaluation.

Many people first encountered AI not as an automation tool, but as an understanding tool.

This was particularly valuable because information overload was already a growing problem long before AI arrived. Leaders, managers and practitioners increasingly found themselves responsible for evaluating more information than they could reasonably process. AI provided a way to accelerate understanding.

Of course, AI does not replace human judgment. AI can help identify possibilities, patterns and perspectives, but people must still determine what is accurate, relevant and important. Good sensemaking still requires human responsibility and accountability.

For security professionals, one of the most important forms of sensemaking is situational awareness. Situational awareness begins with recognizing the presence, behavior and significance of people, objects, activities and conditions within an environment. It continues as new information becomes available and understanding evolves.

In many security operations, situational awareness begins with the recognition of a potential incident and continues throughout assessment, response and resolution. Depending upon the situation, both the speed and accuracy of situational awareness can be critical.

In many security operations, situational awareness begins with the recognition of a potential incident and continues throughout assessment, response and resolution. Depending upon the situation, both the speed and accuracy of situational awareness can be critical. AI is increasingly being used to help identify patterns, recognize anomalies, correlate information from multiple sources and bring important information to attention more quickly. In that regard, AI can significantly enhance the speed and quality of sensemaking.

AI is increasingly being used to help identify patterns, recognize anomalies, correlate information from multiple sources, and bring important information to attention more quickly. In that regard, AI can significantly enhance the speed and quality of sensemaking.

AI and communication

Once people discovered that AI could help them understand information, they naturally began using it to help communicate that understanding to others.

Many professionals have experienced the challenge of knowing what they want to say but struggling to express it clearly. AI has proven particularly useful for improving emails, reports, executive summaries, presentations, procedures, policies, and other forms of written communication.

In many cases, AI can improve organization, clarity, readability, grammar, tone, and audience alignment. It can also help translate technical information into language appropriate for business executives or other stakeholders.

This capability extends beyond simple editing. AI can help people communicate ideas more effectively, helping to reduce misunderstandings and improve alignment among teams and stakeholders.

However, as with sensemaking, responsibility remains with the human user. AI may help improve how something is communicated, but people remain responsible for what is communicated and whether it is accurate, appropriate, and complete.

AI and caring through automation

The third area is perhaps the most interesting because it is often discussed without recognizing its connection to a fundamental human capability.

Caring consists of two related but different concepts: caring about and caring for.

Caring about involves concern, interest and understanding. We usually care about things because we understand why they matter. In that sense, caring about is a natural extension of sensemaking.

Caring for, however, involves action. It is the practical expression of responsibility. Caring for people, assets, systems, projects, commitments and organizational objectives requires ongoing attention and follow-through.

This is where automation enters the picture.

Many organizations have discovered that AI can support caring for responsibilities by helping automate monitoring, reporting, workflow management, incident handling, scheduling, notifications, documentation and numerous other operational activities.

The value is not merely efficiency. The value is consistency.

Managers often describe this benefit as making sure that “no balls get dropped.” AI-assisted automation can help ensure that important tasks are performed accurately, consistently and on time, reducing the likelihood that responsibilities will be overlooked because people are busy, distracted, overloaded or unavailable.

In effect, AI can help people care for more things than would otherwise be possible through manual effort alone.

A lesson learned long ago

There is an important caution, however.

Years ago, during the rise of Business Process Management (BPM), organizations learned that automating a poorly designed process simply allowed mistakes to occur faster and more consistently. Some practitioners summarized this lesson with the phrase, “If you automate a mess, you get more messes faster.”

The same principle applies to AI.

Effective automation depends upon effective sensemaking and effective communication. Before actions are automated, organizations must first understand what should be done, why it should be done and how it should be performed.

Otherwise, AI may simply accelerate existing misunderstandings, communication failures and process deficiencies.

Putting it all together

Viewed from this perspective, AI is not merely a technology platform. It is both a capability amplifier and a security operations force multiplier.

Sensemaking helps people understand.

Communication helps people create shared understanding.

Automation helps people care for responsibilities through consistent action.

Together, these three perspectives provide a practical way to evaluate AI initiatives and identify where meaningful value may be created.

The most useful question about AI may not be, “What can AI do?” Instead, it may be, “How can AI help people achieve better results?”

Organizations that answer that question well are likely to discover that the greatest value of AI is not replacing human capabilities, but helping people apply them more effectively.