Technology Vision 2024

Business will be able to unleash greater human potential, productivity, and creativity in the coming years as a result of an increasingly powerful array of technologies at their disposal. A new era of value and capability has begun, and early adopters and leading businesses are at the forefront. Their strategies share one common thread: technology is becoming more human.

In the end, wasn’t technology made by humans for humans? To create tools that enhance our physical and cognitive abilities is so unique to humanity that some even argue it defines us as a species.

In spite of this, the tools we build are often distinctly unhuman, filling in the gaps we couldn’t fill, and transforming our lives in the process. With automobiles, we gained greater mobility. Cranes allowed us to build bridges and skyscrapers. Music was created, distributed, and listened to by machines.

We have amazing navigational tools, but they still distract us from driving. Technology’s unhuman nature can also be its drawback. Hand tools can lead to arthritis. Years of staring at screens can accelerate vision problems. There has been an effort to create tools that are more ergonomic or easier to use, however, we still make decisions about our lives based on what is best for machines rather than on what is best for us.

It is clear that for the first time in history, we are reversing course by embracing a new generation of technology that is more human, rather than moving away from technology. Intuitive technology, both in design and in nature, demonstrates a human-like intelligence and is easy to integrate into our everyday lives.

Besides affecting the task at hand, generative AI is also starting to fundamentally reshape organizations and markets.

Take into account the profound influence of generative AI and transformer models on our society. What started off as simple chatbots such as ChatGPT and Bard has evolved into a significant factor in enhancing the user-friendliness, intelligence, and accessibility of technology for everyone. While AI previously centered on automating mundane tasks, it is now transitioning to augmenting human capabilities, transforming how we approach our work, and rapidly making advanced technologies and specialized knowledge work accessible to all, rather than just the highly trained or wealthy.

Human technology isn’t limited to AI: It is addressing many of the pain points between us and technology, paving the way for greater human potential.

By designing technology with a human touch, we can reach more people and expand access to knowledge, thereby facilitating ongoing innovation. Think of all the people historically alienated by technology who will be able to contribute to the digital revolution. These people can become new customers and new employees as technology becomes more intuitive.

It is important for leaders to understand the following questions: What products and services are ripe for scaling? What new data is available to you? How can you transform your business? But they will also be at the center of answering questions they may have never expected: What kind of oversight does AI require? Who will be included in the digital transformation? What are our responsibilities to the people in our ecosystem?

In the era of digital transformation, human technology will become central to the success of enterprises as they strive to reinvent their digital core. Human by design isn’t just a description of features, it’s a directive. The pillars of digital efforts are being reinvented by emerging technologies. As technologies such as generative AI, spatial computing, and others mature and scale, digital experiences, data, and products are all set to change.

It is now possible for enterprises to build a strategy that maximizes human potential and eliminates friction between people and technology at this moment of reinvention. AI will power the future, but it must be designed for humans as well. And as a new generation of technology gives enterprises the power to do more, every choice they make matters even more. Is your career a cautionary tale or a role model?

As our relationship with data changes, so does how we think, work, and interact with technology.

A new “advisor” model of human-data interaction is replacing the search-based “librarian” model. As an example, instead of running searches to curate results, people now ask AI chatbots for answers. In November 2022, OpenAI launched ChatGPT, which grew rapidly. ChatGPT was the first to answer questions in a direct and conversational manner, even though large language models (LLMs) had been around for years.

Data is a crucial element in the development of modern digital companies. The emergence of advanced chatbots, equipped with the ability to process large quantities of data and offer guidance, is causing a disruption in this area. The chatbots are capable of utilizing diverse forms of data, recalling past conversations, and making suggestions for future inquiries. In essence, these chatbots can serve as LLM-advisors, granting every employee access to extensive corporate knowledge. This has the potential to unlock the untapped value of data and enable enterprises to fully embrace the potential of data-driven business practices.

There is valuable, unique information that companies want their customers, employees, partners, and investors to discover and utilize. There is a lot of information that is hard to access or distill because we don’t remember the right search terms, we can’t write the query, the data is siloed, or the documents are too dense. This is serious untapped value generative AI can bring to today’s data-driven businesses.

Rather than disrupting how we access data, the true disruption will be in how we transform the entire software industry. What if all digital platforms and apps had generative AI chatbots as their interfaces? Would it not be a core competency for all platforms to read, write, and interact with data?

To truly reap the benefits of generative AI and build the data-and-AI powered enterprise of the future, businesses need to radically rethink their core technology strategy. Those organizations need to rethink how they collect and structure data, their broader architecture, how they deploy technology tools, and what features they include. From the beginning, new practices such as training, debiasing, and AI oversight must be built in.