Generative AI has emerged as one of the prominent highlights of artificial intelligence. Many industries have embraced the diverse use cases of generative AI with the help of tools such as ChatGPT, Stable Diffusion and DALL-E. However, it is important to recognize that the future of generative AI is still far away.
Innovative developments in generative AI can help in introducing substantial changes in business and the functioning of society. With the adoption of AI tools, businesses could accomplish tasks within days that required weeks to complete. At the same time, some reports have suggested that AI takes care of almost 44% of customer service requests.
On the other hand, more people are concerned about data privacy, bias, and ethics in generative AI. As a matter of fact, around 81% of users want a human in the loop to review and verify generative AI outputs.
With only 37% of users trusting AI outputs, the future prospects of generative AI might appear pessimistic. However, brands have been turning to generative AI to improve customer engagement with better efficiency. IDC had predicted that the global AI spending would increase by almost 27% in 2023. Let us unravel some of the prominent predictions for generative AI to determine its potential.
Top Predictions for the Future of Generative AI
The year 2023 would be one of the most noticeable milestones in the history of generative AI as it gained mainstream popularity. As the domain of generative AI moves forward in 2024, it is expected to bring a slew of changes and trends that will transform generative AI and applications.
The responses to queries like “Does generative AI have a future?” draw attention towards research-based predictions. For example, McKinsey research states that generative AI can add almost $4.4 trillion to the global economy every year. Will generative AI stay strong in the long term? Here are some of the important predictions about generative AI that you should watch out for in the future.
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Generative AI Becomes More Mainstream
The most important prediction about the future of AI revolves around the reduction in hype for generative AI. Following the launch of ChatGPT by OpenAI, the domain of generative AI expanded continuously with the introduction of new models. It is important to note that the advanced machine learning algorithms underlying generative AI solutions have been under development for decades. However, no one paid attention to them until the arrival of ChatGPT.
Since late 2022, the world has witnessed multiple iterations of generative AI technology. As a matter of fact, new generative AI models have been introduced multiple times in a month. In March 2023, the domain of generative AI witnessed promising improvements with the arrival of solutions for financial services support and customer relationship management solutions.
Moving forward in 2024, generative AI will no longer be a technological miracle. On the contrary, it would evolve at a rapid pace and come closer to users without any barriers.
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Faster Progress towards Productivity
Artificial intelligence has been designed to replicate human intelligence. Therefore, it is reasonable to assume that generative AI predictions would shed light on the possibilities of achieving human-like performance. McKinsey research suggests that generative AI may achieve a median level of human performance by 2030.
In addition, the predictions indicate that the performance of generative AI would be at par with the top 25% of people completing specific tasks by 2040. Therefore, generative AI can help technology achieve human-like performance in some tasks sooner than expected.
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Automation of Work in Knowledge
The predictions about generative AI also point towards possibilities for automation in the field of knowledge. Better technical capabilities of generative AI can have a formidable influence on the activities of educators, creatives and professionals. The future of generative AI can mirror the past instances in which automation technology affected different physical activities.
Generative AI is likely to have a massive influence on the field of knowledge, particularly in the domains of collaboration and decision-making. Professionals working in the areas of education, the arts, law, and technology can expect faster automation in different aspects of their jobs. Such types of developments would be driven by the ability of generative AI to predict patterns in natural language. On top of that, generative AI could also ensure the dynamic use of patterns in natural language for better results.
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Multimodal Generative AI
One of the most formidable predictions about the future of AI focuses on multimodal generative AI. You can find different types of generative AI tools with distinctive functionalities. For example, some generative AI tools can write, while others can create, hear, see and read. As generative AI expands further, it can address all these tasks at once, such as creating text and images simultaneously. For example, DALL-E 3 can generate high-quality text incorporated in its images.
As a result, it would be a better and more powerful alternative to the competing image-generation tools. Therefore, predictions about generative AI indicate that multimodal generative AI would become the norm. It would help generative AI create in different ways in real-time, just like a human would.
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Interactive AI
The discussions around questions such as “Does generative AI have a future?” also invite attention towards interactive AI. With the arrival of interactive AI, generative AI bots would not only interact with users but also carry out tasks. Interactive AI bots can delegate important tasks to other software as well as people to complete them with desired results.
You can refer to the example of software development to understand the implications of interactive AI. Generative AI has proved to be useful in generating and testing code. The introduction of interactive capabilities in generative AI can help it complete an app development project without human intervention.
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Generative AI Tools for Broader Use Cases
Generative AI tools have proved effective in creating different types of written, audio, video and image content. As a matter of fact, software developers can trust generative AI tools to create code for their new projects. Businesses have been actively developing generative AI apps for leveraging the capabilities of generative AI in these areas. Interestingly, generative AI predictions for the future suggest that generative AI must move beyond walled gardens. In the future, you can expect generative AI apps and tools to target specific industries, use cases and functions. On top of that, the new apps and tools are likely to provide more value than the general generative AI tools.
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Certain Industries Would Reap More Benefits
Generative AI has caught the attention of business leaders in almost every major industry. However, it is important to measure the impact of generative AI on business functions across different industries. According to the generative AI forecast by McKinsey, some industries can achieve more benefits than others.
The impact of generative AI on an industry would depend on different factors, including the significance of business functions, the scale of industry revenue and the mix of business operations. Almost all industries would notice crucial improvements in marketing and sales functions with the use of generative AI. On the other hand, banking and high tech would reap more benefits from generative AI for the acceleration of software development.
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Emphasis on Bridging the Skill Gap
As businesses across different industries establish goals for generative AI, it is important to understand the necessity of skill development. How can organizations embrace AI without the right talent? Therefore, the future of generative AI would depend on how organizations identify workers with generative AI skills.
Generative AI tools can offer enhanced value to early adopters only if they can cross the skill gap. Therefore, businesses would compete against each other to stay on top of the generative AI talent market. Organizations would have to work on improving their talent management capabilities alongside offering rewarding working experiences to generative AI experts.
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Impact of Generative AI on Global GDP
Another important addition to the generative AI forecast for the future revolves around the contribution of generative AI to global GDP. According to McKinsey, generative AI can have a substantial impact on the enhancement of labour productivity across different sectors. Workers can capitalize on the value of such productivity boosts by shifting to other work activities that help them achieve better productivity. Support for training workers to help them learn new skills and change their roles could strengthen GDP growth while ensuring inclusiveness and sustainability.
Challenges Expected in the Domain of Generative AI
The benefits of generative AI showcase that it can emerge as a powerful force of change for business and the everyday lives of people. On the other hand, it is also important to reflect on the challenges that you should expect with generative AI. One of the most prominent challenges in the use of generative AI points to the use of deepfakes.
The detrimental consequences of deepfake technology have been amplified due to the lack of resources to differentiate deepfakes from authentic content. Deepfakes present a major deterrent to the future of AI and machine learning by creating negative sentiments among the public. Unethical use of deepfake technology has immediate and long-term consequences. As a matter of fact, it has far-reaching implications for the society.
Another notable challenge for generative AI emerges in the form of regulations and oversight. Generative AI can be used as a tool for spreading misinformation or creating autonomous and biological weapons. Therefore, it is important to establish regulations that protect the world and ensure the use of generative AI for the positive transformation of society.
On top of that, industry experts must also pay attention to the enhancement of transparency when working on generative AI models. At the same time, it is important to advocate for the ethical use of AI with effective frameworks, policies, and guidelines.
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Final Words
The insights on the future of generative AI reveal its potential to transform different industries and society. Generative AI would become more mainstream and evolve beyond ChatGPT and other general tools. Businesses across different industries can tap into the potential of generative AI to create advanced generative AI apps and tools for specific use cases.
On the other hand, some industries are likely to reap better returns from generative AI in specific business functions. At the same time, it is also important to reflect on challenges for generative AI, such as the use of deepfake technology, lack of regulations and limited transparency in the working mechanisms of generative AI models. Find more insights into the world of generative AI to discover how it will shape up in the future.
