The Future of Information Delivery and AI in 2025
What if your biggest business challenges could be solved before you even identified them? That’s the potential of Artificial Intelligence (AI). The enterprise world is beginning to accept AI as more than a buzzword. They can see value in harnessing their data to solve some of their biggest business problems.
One thing is for sure: data is the key ingredient that enables AI. The more data you can use, the better your insights will be. So where will we see innovations? Will the AI-washing fizzle out? And are we even thinking about this new technology in the right way?
1. We will continue to see infrastructure innovations that support AI.
The digital universe continues to grow at an astonishing pace, hitting an estimated 147 zettabytes by the end of 2024 (via Statista). For perspective, that’s 147 trillion gigabytes—a staggering amount of data. This explosion underscores the need for AI to process and create actionable insights from such a vast ocean of information.
Thanks to advancements in GPUs and faster CPUs, algorithms can now process enormous datasets in record time. At the same time, storage technologies—like higher-capacity flash drives—are enabling faster, more efficient consolidation of data, setting the stage for the next evolution in AI-driven insights.
These are exciting advancements, but infrastructure only exists to support the data. If we are creating information in new ways, will there be new ways to consume these insights?
2. Information delivery will be reimagined.
AI computing advancements such as transformer models have given us a glimpse of what is possible with large language models (LLMs). Om Malik, founder of GigaOM and long-time tech reporter/investor wrote an article about how AI will change the browser as we know it.
He points us in the right direction about what information delivery will look like in the future:
Malik envisions a future where AI doesn’t just passively gather data—it actively connects the dots, delivering insights seamlessly. It’s easy to see this trend developing in tools we already use today. He gives an example of having a DietBot to deliver a data stream customized to you that includes an analysis of your eating patterns, health goals, and dietary requirements that match restaurants in real time.
My Samsung watch does a lot of that now, but I have to manually provide much of the information. I have to track my meals and water intake with a different app (Yazio) that I connected to my watch’s app. I weigh in with a digital scale that I also connected to the watch app. The watch can calculate my steps and heart rate.
But my blood pressure monitor can’t connect to my watch, so I have to enter that reading manually. It also can’t connect to my Kardia (used to check for atrial fibrillation). How cool would it be to have a DietBot to do all the work for me? Even better – what if I could tap my watch to my doctor’s tablet and she could get all my latest readings? What if she could subscribe to my data stream when I felt sick, for a better diagnosis?
That’s what is coming – data streams we’ll need to subscribe to in some way. The question becomes how will we consume it? Will it be a new type of browser, an app on your phone (or watch, or TV)? I think we’ll see innovation in how we consume these data streams in 2025.
3. AI hustlers will be everywhere.
With the AI market predicted to hit $1 trillion by 2027, it’s no wonder the bad actors are beginning to circle like sharks.
AI-washing, where companies exaggerate the AI capabilities of their products, is already rampant. Maybe you’ve seen an “AI” version of a product that has merely added a chatbot. The Federal Trade Commission (FTC) is cracking down on exaggerated AI claims, such as the infamous 'world’s first robot lawyer,' which failed to deliver on its promises—mainly because it lacked real lawyers!
Cybercriminals aren’t far behind, using generative AI to launch scams that are more sophisticated than ever. Ransomware gangs are already on the AI bandwagon, probably looking for better ways to a big payout (up to 75% of ransom payments are over $1 million).
AI has lowered the barrier to entry to new hackers. Generative AI has helped these bad actors create more believable text, images, audio, and video to hook their victims. Once in, they are able to pinpoint the high-value data for exfiltration (and higher ransoms).
The bad guys are usually first adopters of new technology. And with so much money on the line, they are only going to double down on their AI efforts.
Adapting to the Changing AI Landscape
The basics of data management are not going to change. The Association for Computing Machinery (ACM) lays out the 7 Principles of an Organizational Data Strategy as governance, data content, data quality, data access, data management, data informed decision making, and analytics.
These steps won’t change because AI processes are using the data. But it will be easy to forget the things we learned as we get caught up in the excitement of new technologies to deploy. So remember your training!
The AI revolution is here, and it’s changing the way we work, think, and interact with information. Living through technological changes can be really exciting. We are bearing witness to new technologies that are driving an information revolution. The best way to enjoy this ride is to learn more about these technologies and explore new ways to consume data streams.
After all, the ride is only beginning.
Got ideas for how AI will reshape the way we consume data? Are you building one? Join the conversation on the Tech Aunties podcast—reach out on LinkedIn!
What if your biggest business challenges could be solved before you even identified them? That’s the potential of Artificial Intelligence (AI). The enterprise world is beginning to accept AI as more than a buzzword. They can see value in harnessing their data to solve some of their biggest business problems.
One thing is for sure: data is the key ingredient that enables AI. The more data you can use, the better your insights will be. So where will we see innovations? Will the AI-washing fizzle out? And are we even thinking about this new technology in the right way?
1. We will continue to see infrastructure innovations that support AI.
The digital universe continues to grow at an astonishing pace, hitting an estimated 147 zettabytes by the end of 2024 (via Statista). For perspective, that’s 147 trillion gigabytes—a staggering amount of data. This explosion underscores the need for AI to process and create actionable insights from such a vast ocean of information.
Thanks to advancements in GPUs and faster CPUs, algorithms can now process enormous datasets in record time. At the same time, storage technologies—like higher-capacity flash drives—are enabling faster, more efficient consolidation of data, setting the stage for the next evolution in AI-driven insights.
These are exciting advancements, but infrastructure only exists to support the data. If we are creating information in new ways, will there be new ways to consume these insights?
2. Information delivery will be reimagined.
AI computing advancements such as transformer models have given us a glimpse of what is possible with large language models (LLMs). Om Malik, founder of GigaOM and long-time tech reporter/investor wrote an article about how AI will change the browser as we know it.
He points us in the right direction about what information delivery will look like in the future:
Malik envisions a future where AI doesn’t just passively gather data—it actively connects the dots, delivering insights seamlessly. It’s easy to see this trend developing in tools we already use today. He gives an example of having a DietBot to deliver a data stream customized to you that includes an analysis of your eating patterns, health goals, and dietary requirements that match restaurants in real time.
My Samsung watch does a lot of that now, but I have to manually provide much of the information. I have to track my meals and water intake with a different app (Yazio) that I connected to my watch’s app. I weigh in with a digital scale that I also connected to the watch app. The watch can calculate my steps and heart rate.
But my blood pressure monitor can’t connect to my watch, so I have to enter that reading manually. It also can’t connect to my Kardia (used to check for atrial fibrillation). How cool would it be to have a DietBot to do all the work for me? Even better – what if I could tap my watch to my doctor’s tablet and she could get all my latest readings? What if she could subscribe to my data stream when I felt sick, for a better diagnosis?
That’s what is coming – data streams we’ll need to subscribe to in some way. The question becomes how will we consume it? Will it be a new type of browser, an app on your phone (or watch, or TV)? I think we’ll see innovation in how we consume these data streams in 2025.
3. AI hustlers will be everywhere.
With the AI market predicted to hit $1 trillion by 2027, it’s no wonder the bad actors are beginning to circle like sharks.
AI-washing, where companies exaggerate the AI capabilities of their products, is already rampant. Maybe you’ve seen an “AI” version of a product that has merely added a chatbot. The Federal Trade Commission (FTC) is cracking down on exaggerated AI claims, such as the infamous 'world’s first robot lawyer,' which failed to deliver on its promises—mainly because it lacked real lawyers!
Cybercriminals aren’t far behind, using generative AI to launch scams that are more sophisticated than ever. Ransomware gangs are already on the AI bandwagon, probably looking for better ways to a big payout (up to 75% of ransom payments are over $1 million).
AI has lowered the barrier to entry to new hackers. Generative AI has helped these bad actors create more believable text, images, audio, and video to hook their victims. Once in, they are able to pinpoint the high-value data for exfiltration (and higher ransoms).
The bad guys are usually first adopters of new technology. And with so much money on the line, they are only going to double down on their AI efforts.
Adapting to the Changing AI Landscape
The basics of data management are not going to change. The Association for Computing Machinery (ACM) lays out the 7 Principles of an Organizational Data Strategy as governance, data content, data quality, data access, data management, data informed decision making, and analytics.
These steps won’t change because AI processes are using the data. But it will be easy to forget the things we learned as we get caught up in the excitement of new technologies to deploy. So remember your training!
The AI revolution is here, and it’s changing the way we work, think, and interact with information. Living through technological changes can be really exciting. We are bearing witness to new technologies that are driving an information revolution. The best way to enjoy this ride is to learn more about these technologies and explore new ways to consume data streams.
After all, the ride is only beginning.
Got ideas for how AI will reshape the way we consume data? Are you building one? Join the conversation on the Tech Aunties podcast—reach out on LinkedIn!
