Summary

Artificial intelligence becomes most useful when it helps people reconnect information scattered across calendars, email, documents and other systems. Drawing on a real client-review task, the article shows how AI can recover forgotten context, connect related work and organize information without replacing human judgment. It argues that the next phase of AI will depend on both deeper integration with everyday tools and sufficient trust for people to grant those systems access while retaining human approval over consequential actions.

Can AI Actually Help Me?

By Mustafa Tameez
AUG 25, 2026

A few years ago, I was on a regular rotation as a cable news commentator. For a while, I appeared four to six times a month.

I became a useful guest for bookers and producers because I could speak about three subjects that regularly drove opinion television: national security, through my work with the Department of Homeland Security; policing and communities, after my firm helped provide implicit bias training to all 5,200 Houston police officers; and politics, where I had spent most of my career.

That made me an easy booking across a wide range of news stories.

During that period, a distant relative watched a couple of my interviews and called my mother to ask what I actually did for a living.

My mother said, “I really don’t understand what he does either. All I know is he’s not a doctor, and he can’t help me.”

It was funny because it was true.

Lately, I have been writing a great deal about artificial intelligence: what it means for energy, markets, work, investing and the future of Texas. Several friends have now given me their version of my mother’s response.

It is great that you understand all of this, they tell me. But can you tell me something that will actually help me?

Fair enough.

So rather than explain what artificial intelligence may someday do to civilization, let me tell you what it did for one task I had been dreading.

My Life in Half-Hour Increments

Like many of my contemporaries, my calendar is not entirely mine.

My wife has access to it. My assistant has access to it. Members of my leadership team can see much of my professional life divided into half-hour increments. Sometimes I learn about a meeting because someone tells me what has already been added or moved.

We also use the calendar to reconstruct time for billing and client reporting. There may be notes, emails and documents scattered elsewhere, but the calendar is often the clearest record of where I was, whom I was speaking with and what demanded my attention.

So much of my life can be explained by what appears on my calendar.

I recently discovered that I began using Google Calendar in 2007. I did not remember when I started. My calendar remembered for me.

A few months ago, I connected ChatGPT to my calendar and asked it to look back through years of entries. I needed to identify everything I had worked on for a particular client over the course of a year.

Normally, that would have been a monumental task: searching appointments, opening old email threads, digging through the shared drive and relying on an imperfect memory. It was exactly the kind of assignment I tended to postpone.

I expected it to save time. It did, but that was not the part that surprised me.

It surfaced meetings and workstreams I had forgotten, allowing me to see the year as a whole rather than rely on whatever remained fresh in my memory. It made me more thorough than I probably would have been on my own.

AI did not merely help me do the work faster. It helped me see the work more clearly.

What surprised me was how new this still felt. Connecting a calendar or email to AI is not yet something most of us think to do.

Then I Started Wondering

Once I saw what it could recover from my calendar, I had another thought: What if I could do the same thing with my email?

The calendar could tell me when a meeting occurred and how often we engaged with the client. Email could reveal what people requested, what concerns surfaced, what decisions were made and which questions remained unresolved.

Then came the next thought: What if I could also search the shared drive?

Now I had three different records of the same relationship.

The calendar showed where the time went. Email showed what people said and decided. The shared drive showed what we actually produced.

Each system held a different part of the story. For years, software has scattered our lives across separate applications. AI becomes useful when it can reconnect them.

The work had always been there. What had been missing was a practical way to see it together.

That changed the nature of the assignment. A task I had dreaded became something I was excited to examine, not because the computer would make the decisions for me, but because I could begin with the whole record rather than a handful of fragments.

From What to Why

Once the meetings, messages and documents were assembled, I could begin grouping the work into larger themes.

Some meetings that had seemed unrelated were actually part of the same initiative. Certain problems appeared repeatedly during the year. Some projects had expanded far beyond their original purpose. A few commitments appeared to have been made but never fully completed.

The first question had been straightforward: What did we do?

The more valuable question became: Why were we doing it?

A calendar can produce a chronology. It cannot, by itself, explain the purpose behind the activity. A list of meetings may show that people were busy, but it does not tell you whether the work was connected to a strategy, whether that strategy changed or whether everyone involved understood the same goal.

AI is often described as a machine that will think for us. That is not what happened here.

It gathered what I had forgotten, connected what had been separated and organized what had become difficult to see. It did not tell me what the work meant. It gave me a fuller record from which to make that judgment for myself.

Its memory helped me use my own judgment more effectively.

That may be one of the most practical uses of AI. It can help us recover the context that modern life has broken apart across dozens of systems.

Three Things Worth Trying

The lesson is not that everyone needs to reconstruct a year of client work. It is that the same method can be applied to many ordinary problems.

First, ask AI to find the pieces.

You might ask it to identify every meeting you had with a client, school, contractor or organization during a particular period.

Then ask it to connect the pieces.

Compare those meetings with the relevant emails, notes and documents. Look for decisions, recurring concerns and unfinished commitments.

Finally, ask what the pieces mean.

Group the information into larger themes. Ask what changed, what remains unresolved and what the activity was ultimately trying to accomplish.

The same approach could help someone prepare for an annual review, reconstruct a long home renovation, organize months of communication with a school or understand a family project that has spread across text messages, email and shared documents.

There are smaller uses as well. I often develop ideas by talking, and I can now speak a disorganized thought into my phone and ask AI to turn it into an outline, an email or a list of assignments. You can now upload a photograph and describe the change you want instead of learning complicated editing software.

Ordinary language is becoming the interface.

This is more than a convenience. For decades, software forced us to adapt to its interface: menus, folders, apps and file paths. What is changing now is the reverse. We can increasingly describe what we want in ordinary language, and the system adapts to us.

That may turn out to be one of the most important changes in how people actually use technology.

Why I Finally Switched to Apple

Long before Android existed, I was the kind of person who would eventually become an Android user. When I first started using computers, I took pride in being on the IBM side. Apple users seemed almost like members of a cult. When smartphones came, Android felt like the natural choice: more flexibility, more choice, less dependence on one company.

A few years ago, I switched to an iPhone because I wanted my phone, laptop and iPad to work together. The ecosystem I had resisted became the reason I switched.

Convenience was not the only factor. I also believed Apple had built a stronger reputation around privacy and security. That did not mean I thought Apple was perfect. It meant I was more comfortable letting one company connect more parts of my life.

Connection made the switch useful. Trust made the switch acceptable.

Artificial intelligence is approaching the same threshold.

The more access it has to our calendars, email, files, photographs and conversations, the more useful it can become. But each connection also requires us to place more trust in the systems behind it.

My rule is simple: Give AI enough access to help, but not enough authority to surprise you. Let it search, summarize, organize and prepare, while keeping human approval over anything sent, published, purchased, deleted or shared.

What Comes Next

The next stage of AI is not simply a chatbot with better answers. It is a system that can understand that a meeting, an email thread and a final document may belong to the same continuing story.

Today I still have to ask it to reconstruct that story. The systems are beginning to get better at recognizing when related meetings, threads and documents belong together. The next step is for them to notice that an annual client review is approaching, gather the relevant material, flag unfinished commitments and prepare a briefing for my approval.

The future I find useful is not one in which AI quietly takes control of our lives. It is one in which AI notices what needs attention, assembles the context and prepares us to act.

For most people, that will matter more than whether a machine can win another test of intelligence. Technology enters our lives through ordinary moments of relief: something found, something remembered, something difficult made manageable.

My Mother’s Test

My mother died on December 16, 2024.

I loved her deeply, but she was tough. She loved us fiercely, yet she never confused love with flattery. She knew how to separate the wheat from the chaff.

When she said she did not know what I did and only knew that I was not a doctor and could not help her, she was joking, but she was also applying her usual test: What good is any of this to an ordinary person?

In the end, consumers are a lot like my mother.

We may be impressed by what artificial intelligence can do. We may listen to predictions about how it will transform companies, markets and entire societies. Eventually, though, we apply a simpler and more unforgiving test:

Can it actually help us?

The answer is beginning to be yes.

Not because AI can explain everything about the future, but because it can help us recover parts of our own lives that have become divided, forgotten or difficult to understand.

It does not have to transform civilization by tomorrow morning.

For most people, it first has to make tomorrow morning a little easier.

Frequently Asked Questions

Sources and Further Reading

1. OpenAI — Google App for ChatGPT: Data Controls FAQ
   Explains how ChatGPT can access connected Google services, how permissions work and how data retrieved through those connections is handled.
   https://help.openai.com/en/articles/10408842
2. OpenAI — ChatGPT Apps with Sync
   Explains how synced apps allow ChatGPT to retrieve relevant information from connected sources while respecting existing user permissions.
   https://help.openai.com/en/articles/10847137
3. OpenAI — ChatGPT Agent
   Describes how AI systems can interact with connected websites and apps while also outlining the privacy and security risks associated with granting access to sensitive information.
   https://help.openai.com/en/articles/11752874-chatgpt-agent
4. OpenAI — Security and Privacy
   Provides an overview of OpenAI’s security practices, privacy controls and protections for consumer and business data.
   https://openai.com/security-and-privacy/
5. Microsoft — Outlook Email and Calendar App for ChatGPT
   Explains how connected Outlook email and calendar services can be searched and used for tasks such as summarizing messages, identifying action items and reviewing meetings.
   https://help.openai.com/en/articles/12512241-outlook-email-and-calendar-connectors-for-chatgpt
6. OpenAI — Terms and Policies
   Provides links to OpenAI’s privacy, service and connector policies governing how connected services and user information are handled.
   https://openai.com/policies/