AI integration and MLOps

Artificial intelligence (AI) has significantly impacted how businesses operate, including the accounting, media, aerospace, manufacturing and healthcare industries, to name a few. But these changes didn’t happen all at once. Several key breakthroughs and waves of innovation have periodically spurred AI adoption over the technology’s history. As the hype around the last dies down, enterprises begin looking for the next.

At this point, it’s become clear that AI will define the future of business. However, how that shift will happen remains uncertain. Understanding where AI could go from here will help companies invest in the right technology and prepare accordingly to stay competitive amid innovation.

The State of AI Today

The most recent AI evolution is undoubtedly generative AI. OpenAI’s chatbot platform ChatGPT is the fastest-growing consumer application in history, reaching 100 million monthly users just two months after its launch. Several imitators and competitors have emerged in the wake of this success.

Google began publicly testing a conversational generative AI model called Bard in February. Around the same time, Meta CEO Mark Zuckerberg announced plans to make the company a leader in generative AI in a quarterly earnings report. In the meantime, several organizations have teamed up with OpenAI to integrate ChatGPT into internal and customer-facing processes.

AI gained significant momentum in 2020 as businesses accelerated digital transformation plans amid the COVID-19 pandemic. However, generative AI’s rise to mainstream appeal was far faster and more dramatic. ChatGPT and its competitors have made AI more accessible and versatile than ever — or have at least shown the potential to — so the world has likely only scratched the surface of their impact.

What Could the Next Step Be?

Generative AI is an impressive step forward in AI technology, but it’s not the pinnacle of what it can achieve. While it can be difficult to predict what specific branches of AI will spur the next wave of innovation, the next steps may already be on the horizon.

Multimodal Generative AI Models

Multimodal generative AI is a natural progression from where AI is today. These models build on the same principle of generating data instead of simply analyzing it but go further by encompassing a broader range of content types. ChatGPT can write text, and many AI models can create art today, but tomorrow’s platforms will do both under a single umbrella.

Generalist AI models already exist but are limited. DeepMind unveiled a multimodal model called Gato in late 2022 that can control robotic arms, generate text, create images and more. However, it fails to excel in any of these categories as much as a specialist model. Further research and development in this area could overcome these challenges.

Multimodal models are becoming an increasingly viable future as generative AI grows. It’s a necessary step forward, too. Enterprises using a single model for multiple AI functions will minimize SaaS sprawl and make AI implementation more cost-effective.

Artificial General Intelligence

The next big AI evolution could also take the form of artificial general intelligence (AGI). While multimodal generative models will likely become a reality first, AGI will have a more disruptive impact on enterprises.

An AGI model can theoretically perform any task the human brain can. That’s a broad category open to much interpretation, but many experts define it as a system that can devise an effective solution in an unfamiliar situation. These AI models that can improvise may be a far cry from today’s technology, but companies like OpenAI have explicitly cited them as a goal.

When Can Enterprises Expect These Changes?

When they take hold, multimodal generative models and AGI will likely be significant disruptors in the AI industry. However, when that shift will happen is less certain.

Given the level of today’s generative models, multimodal versions may not be far off. Experts predict that 70% of global organizations will use AI in at least one area by 2030. This rising investment in AI technology will fuel research and innovation if that proves accurate. From a technological standpoint, it’s reasonable to expect reliable multimodal models within the next five to 10 years.

Whether this technology will become available as soon as it’s technologically possible is another matter. ChatGPT’s success has also drawn attention to its shortcomings, including factual inaccuracies and concerns over plagiarism and bias. Given these risks, generative AI may face legal and regulatory hurdles in the future, slowing its development.

The timeline for AGI is likely longer. According to a recent survey, half of AI experts today believe there will be at least a 50% chance of human-level AI existing by 2061. Given AGI’s disruptive potential, it’s likely to face even more significant social and legal challenges than generative models.

AI’s Future Is Exciting but Uncertain

Future AI developments look promising. AGI and multimodal generative AI models will have far-reaching impacts on everyday life and business, but these technologies still carry much uncertainty.

Enterprises can expect AI to experience another significant step within the next decade and even more disruptive changes over the next 50 years. However, as this technology advances, it will encounter new obstacles, making it difficult to determine when the tipping point will be. If AI developers can prepare for and overcome these challenges, AI’s next wave of disruption could come sooner than many expect.