As industries race to find ways to operationalize AI into their businesses I've found that many of my counterparts are approaching this new technology as a solution looking for a problem which is understandable because of the nature of which LLM (Large Language Models) and ML (Machine Learning) interface with humans.
The quintessential challenge in technology remains information management. The data deluge that we're experiencing is unlike anything in human history, and it presents unprecedented challenges. While the tech industry has grappled with the question of how to manage information since the days of the operating system wars, the advent of AI presents a monumental opportunity to finally get it right. One compelling solution to this age-old challenge is the concept of the "everything app," an AI-driven, one-stop-shop that prioritizes and manages data for us allowing an automated way to sift through, prioritize, and manage the myriad strands of information that come our way.
The Complexity: Balancing Fidelity, Timing, and Channels
As identified in previous studies such as those by IDC (International Data Corporation), the sheer volume of data generated in general and consumed by humans particularly presents us with three core challenges: delivering the right information at the right time, at the appropriate fidelity, and through the most effective channel. “The Global DataSphere is expected to more than double in size from 2022 to 2026” according to IDC. While that in itself is stunning, the fact remains that the pivotal issue must be the characterization of quality data which itself is not a static definition.
Further, there's are so many channels through which we as a community interact, that are all fighting to grab our attention. This is of course, driven by the humans and brands’ desire to surface their story, but it is compounded by the very nature of the systems and networks on which they exist whether they are social networks, email, phone, SMS, or DMs. In many cases, the dialogue that we have with the world about certain domains of our lives comes exclusively through these channels and without a more effective way of placing our attention in the right place, people become overwhelmed or worse, apathetic, to things going on around them.
Learning From History
Whether it was the operating system wars, the browser battles, or the explosion of social media, the key challenge and indeed the way to carve out market share for technology companies has been to present information in a manageable and effective manner. Each of these milestones has contributed something meaningful to the way we experience and interact with technology today. In each case, the tech industry ultimately found a way to create more user-friendly experiences, although the problem of information overload has never been completely solved and ultimately has changed through the evolution of society’s interaction with technology and the information that it manages (which at this point is all of it).
The AI Revolution: The Game-Changer
Artificial Intelligence has changed the narrative entirely. AI technologies have the potential to bring in trillions in value annually. With machine learning and sophisticated algorithms, AI can offer personalized, timely, and relevant solutions in ways that were previously unimaginable. On top of that, generative AI in itself is clearly going to end up being a cornerstone in the way that content is created from here on out. It has offered the opportunity to augment the voice of everyone who has been held back in trying to get their unique story told but will almost certainly push. However, it will result in massive amounts of unnecessary content. Because of this, users will need and want their own technology to adapt to make their lives easier, simpler, and less noisy. A pragmatic and thoughtful approach to the lens through which we interact with the digital space is required.
The 'Everything App' — A Real-world Scenario
Let’s consider an example to understand how an AI augmented “everything app” could be a game-changer:
Case Study: The Integrated Calendar
Imagine the "everything app" integrated with your calendar, both personal and professional. It knows you have a project deadline at work in two weeks and a family event the weekend before that. Rather than simply reminding you of these events, it starts to prioritize information and tasks that will help you meet that work deadline well in advance.
Surfacing Critical Information: Three days before your family event, it starts to surface essential project-related emails and files, knowing that you historically prefer to wrap up work before personal engagements.
Balancing Priorities: The AI algorithm also understands that you usually prioritize family time during the weekend. It avoids overwhelming you with work-related information, subtly shifting the balance to prioritize family-related activities and information as the weekend approaches.
Timely Reminders and Insights: With ample time before the deadline, it starts sending you reminders about the project's smaller tasks that you need to wrap up. It can even pull insights from your past projects to suggest the fastest way to complete these tasks, based on your historical performance and work habits.
This way, the app doesn't just serve as a management tool; it becomes an intelligent assistant that understands your life's ebb and flow, helping you navigate both professional and personal landscapes more effectively.
Evolving Platforms: Microsoft Teams, Slack, and Twitter (X)
Companies like Microsoft, Salesforce, and Twitter (now known as "X") have already begun to evolve their platforms in this direction. For example, Microsoft Teams could easily extend its enterprise-focused capabilities to include personal project management, facilitated by the Microsoft ecosystem's AI prowess. Slack, following its acquisition by Salesforce, has already begun transforming into a more comprehensive work-management platform, enhanced by Salesforce's AI capabilities.
As these companies evolve their own offerings to react to this change, there are plenty of ways that they will bring these technologies to current and future clients. Companies will need to consider various strategies for getting their evolved platforms adopted from the tactical level even without a massive shift in the way that companies perform their own work.
The experience must be designed with the end-user in mind, offering a clean interface and easy navigation. Compatibility with other commonly used platforms will make adoption easier for clients who are already invested in specific ecosystems. Assurances of robust data security and compliance with regulations could provide an edge in attracting enterprise clients. Finally, offering highly customizable solutions can attract different market segments, from individual users to large enterprises. These are the categories that companies will be competing with each other for the near future to bring their customers and users on their own journey toward the future.
Solving Problems We Create
We are standing on the threshold of a transformative era. The hype around AI, the potential shift in the way that technology exists, the possibility of an "everything app", and the expectation of the massive shift in the way our lives are organized and managed both at work and home offers a potential solution to the ever-present challenge of managing our increasingly complex digital lives. Through intelligent, AI-driven prioritization and management, this new breed of applications could help us make sense of the world around us in a more organized, less stressful manner. The convergence of our professional and personal lives into one streamlined, intelligently managed experience isn't just a possibility; it's an imminent reality.
Commenti