What year 2 of the generative AI craze will look like, according to 41 experts

Today marks the one-year anniversary of ChatGPT’s public debut. The chatbot, which was released to the public as a sort of research sandbox, helped catalyze an massive AI arms race in Silicon Valley and a corresponding push for AI integration across products and sectors.

To mark ChatGPT’s anniversary, we asked 41 AI experts, business leaders, and other stakeholders a simple question: How will generative AI tools like ChatGPT and Midjourney be applied over the next year to best help businesses function more efficiently or assist individual consumers? Here’s what they said. Their quotes have been edited for length and clarity.

Ben Bajarin, principal analyst, Creative Strategies

Most of our conversations at the moment are around how businesses will look to use generative AI to increase their organization’s overall employee productivity. We have been talking to CIO/CTOs/ITDMs to understand how they are thinking about this, and where I believe most organizations will use GenAI is around domain-specific large language models/agents trained around their data for specific departments. Call center and customer support is one where we are seeing real deployments today and increased productivity of call center agents and increased customer satisfaction. But ultimately, we believe every corporate workflow will benefit and be infused with AI.

Jeremiah Owyang, partner, Blitzscaling Ventures

By the end of 2024, our digital lives will be transformed, starting with our daily communications. Every individual at home or work will have an AI agent to manage their emails. Initially, it will filter, highlight, and summarize messages. As the agent analyzes our history, understands context, and incorporates our feedback, we will, over time, trust it to respond on our behalf using a defined set of guidelines and rules. When you want to really get someone’s attention, you may indicate this is an organic artisan email, written by me, a human!

Clara Shih, CEO, Salesforce AI

2024 will be the year that generative AI will go from experimental pilot to standard operating procedure at many companies. The first use cases will be customer service, sales, marketing, and software development. To do this, companies will need to put in place three foundational ingredients: first, a secure data cloud for all of their structured and unstructured data; second, a generative AI trust layer that provides data security, privacy, ethical and regulatory guardrails on top of large language models; and third, a copilot platform to build and customize prompts, actions, and models.

Joe Atkinson, chief products and technology officer, PwC

A happier workforce leads to better business outcomes, and I’m optimistic about the role GenAI will play in contributing to a more personalized employee experience that will increase engagement, satisfaction, and productivity. There’s no doubt we’ll continue to see companies more aggressively roll out AI training and experimentation programs next year alongside growth in the most practical GenAI use cases that save organizations time and money, including more personalized customer support and recommendations, high-quality content generation, and workflow automation.

Grace Isford, partner, Lux Capital

Generative AI tools are already serving as efficient copilots in numerous functions, including coding, customer support, and search. We are witnessing a significant acceleration in routine tasks like knowledge retrieval, information summarization, and task automation. This trend is expected to grow, with AI copilots becoming increasingly sophisticated and evolving into long-term agents capable of performing comprehensive business functions and enhancing multistep workflows. We’ll also see the growth of multimodal AI applications become commonplace in everyday business operations. This includes the integration of speech, video, and image-processing capabilities. 

Brendan Burke, emerging technology analyst, PitchBook 

VC investment in generative AI for coding has increased 357.4% this year to nearly $400 million due to the success of GitHub Copilot in code recommendations. The ability to automate software development is beginning to reach beyond current software developers to product designers and operational teams. Usage of AI coding tools will become widespread among these functions next year. Adding to this momentum, new foundation models coming out next year will learn from the entire software development process to make anyone capable of deploying an application from start to finish. 

Oded Netzer, professor, Columbia Business School

A good application of [generative AI] is in the domain of medicine. Studies have shown that physicians spend much of their time on updating electronic records and desk work. Physicians often complain that they have difficulty finding time with their patients. If chatbots can create transcripts of conversations between the physician and the patient (including doctor-provided verbal instructions) and enter them into the patient record . . . doctors may be able to spend more time with their patients and possibly see more patients.

Kara Sprague, EVP and chief product officer, F5

One of the biggest beneficiaries of efficiency and productivity from generative AI will be overworked security teams. These teams are stretched because of a cybersecurity-skills gap that has created a shortage of 3.5 million people. AI can automate processes and improve the efficacy of tools that allow security teams to better secure today’s complex networks and applications, while more quickly detecting, analyzing, and responding to threats in an increasingly AI-driven threat landscape.

Pablo Abreu, chief product and analytics officer, Socure

Generative AI technology has given rise to more sophisticated attacks by fraudsters—from sending phishing emails that look authentic to creating impeccable fake government-issued documents.  In the next year, I am expecting organizations to creatively adapt generative AI solutions to quickly help stop these deepfakes and more sophisticated identity fraud attacks before any harm is done. Generative AI must be a tool in your arsenal for efficiency and risk mitigation. 

David Haber, cofounder and CEO, Lakera

As AI training costs continue to drop, watch for a major shift: businesses of all sizes tailoring models like ChatGPT to tackle challenges unique to their operations. Whether it’s engineering, marketing, or HR, AI models will evolve into specialized assistants. Beyond individual tasks, these AIs will . . . also assist in strategic decisions. It’s not just boosting efficiency; it’s the start of a new business playbook being written, akin to the creation of the internet.

Timothy Young, CEO, AI startup Jasper

This year, businesses began experimenting with generative AI to achieve greater efficiency in their work. That was a good start, but I believe that in 2024, the story will shift from faster outputs to better outcomes as companies more fully adopt AI and use copilots that bring analytics and self-optimizing content into the mix.

John Blevins, adjunct professor, Cornell University business school

Over the next year, the AI hype will continue to grow, and the AI return on investment will remain elusive for many organizations. Right now, almost every organization is talking about investigating and determining their AI strategy, some with real-budget amounts being applied to their initiatives. However, most businesses do not have enough data to train effective, trustworthy algorithms quickly enough to see a return on investment in 2024 from these initiatives. The payback will come in time. 

Katie Gardner, partner, Gunderson Dettmer law firm

Professional service providers (including lawyers) will need to rethink their business models, especially if they are heavily reliant on revenue generation in areas that can be reliably and efficiently replaced by AI—e.g., document review and diligence. The traditional pyramid model where you have a high volume of junior associates doing these tasks may no longer be economically feasible. There will be widespread upskilling as many tasks will no longer require humans to execute them. Similar to the prior industrial revolutions, most existing necessary functions of organizations will transform in a dramatic and material way.

Subutai Ahmad, CEO, Numenta

So much has changed in one year! ChatGPT has spotlighted AI on a massive scale, and created tremendous excitement, but it is clear we’re just at the beginning of what’s possible. By working directly with companies putting LLMs into production, we’re seeing both the potential and the challenges. Looking ahead, bridging the gap between the hype and real AI-enabled applications will require solutions that are simple, scalable, and cost-efficient, and that enable companies to have complete control over their data and models.

Tim Davis, cofounder and president, Modular (ex-Google Brain)

I would expect GenAI adoption to accelerate as a reflection of the cost side of the balance sheet with deep penetration across high-cost functions like sales, marketing, customer operations, engineering, and product. You are already seeing this happening as GenAI revolutionizes content production, customer interactions with chatbots, search engine optimization, product knowledge discovery, engineering code generation, in addition to product design and testing among so many other areas. These are real and direct use cases, not technological hype, and they are delivering incredible business value that will only quickly accelerate in the months and years ahead.

Anna Marie Wagner, head of AI, Ginkgo Bioworks

Consumer-facing AI tools are getting extremely powerful in areas of obvious judgment (cleaning up mismatched names in a database, for example, or analyzing written survey results) that have historically generated huge time sinks for highly skilled employees, such as financial analysts, sales reps, or strategy consultants. Large language models will continue improving on their ability to . . . accurately synthesize raw data into usable formats so that these professions can spend more time on insights rather than analysis.

Arun Chandrasekaran, AI analyst, Gartner

Generative AI can enable creating new, unique outputs across a range of modalities (i.e., text, images, code, audio, video), which can be a transformative opportunity. Machine creativity is in the early stages and can be harnessed in many ways to speed the development of new products and build competitive differentiation.

Kiran Raj, practice head, disruptive tech, GlobalData

For individual consumers, generative AI opens doors to personalized services, from shopping recommendations to educational assistance. ChatGPT can serve as a virtual tutor, while Midjourney can assist in creative endeavors like art and music. Financial and healthcare guidance, lifestyle management, and travel planning are other areas where AI can deliver significant benefits, offering personalized advice and suggestions. As these tools integrate more deeply into platforms and services, they are set to enhance efficiency, creativity, and convenience for businesses and consumers alike.

Rob Enderle, principal analyst, the Enderle Group

Expect to see these tools used heavily for customer support, telesales, and for customer relationship management. Initial studies have shown that the effective use of these tools for customer interface purposes increased customer loyalty, satisfaction, and retention, reducing customer churn with positive impacts on both the top and bottom line.  

Catherine Roggero-Lovisi, CEO, Modern Meadow

AI tools are particularly valuable when a large amount of clean data is available and where connections and correlations between those data sets can be mapped relatively easily. With this in mind, in the Biomaterials space where Modern Meadow operates, AI tools will be helpful in many ways. First, supporting consumers when navigating overwhelming amounts of information on product and material. AI tools will allow them to easily find the most sustainable options while avoiding being swayed by fake news.

Moez Draief, manager, Mozilla.ai

Even one-year predictions are complex when it comes to such transformative and fast-evolving technology like AI. With their state-of-the-art semantic capabilities, ChatGPT-like models have the potential to transform the search experience for customers. This decades-old transverse problem faces today’s issues related to data privacy or hallucination and factuality. Research that will be conducted over the next year, both at the fundamental levels of AI science and on the engineering side, will enable for customers and businesses to better make use of their data.

Steve Won, chief product officer, 1Password

The 2024 election cycle will pollute our virtual town square with disinformation and disillusionment at unprecedented levels. Generative AI will be the ringleader, driving a steady flow of social engineering that will foster an unprecedented environment of distrust online. The upside is that this will be the tipping point for rejuvenating how we connect with each other. Big Tech, security, and government will need to come together in the coming years to develop meaningful solutions to clean up the virtual town square and reduce disinformation from our lives.

Peter Chapman, president and CEO, IonQ

In the upcoming year, I foresee that AI tools like ChatGPT and Midjourney will continue to transform how businesses operate and enhance their customer experiences. What really excites me is the potential of new quantum techniques to make these AI models faster and more efficient, ultimately reducing costs and environmental impact. This will make these AI models more accessible and speed up their adoption in the business world.

Sridhar Ramaswamy, SVP of AI, Snowflake

Over the next year and beyond, we are going to see language models with specialized skills for SQL writing and API calling become glue layers in enterprise interoperability between applications. These have the potential to break down silos-—today, each app lives in its own world—and create a whole new category of mashup applications that are quick to create and effective in practice. The technology for these applications and autonomous agents to automatically take actions is still early, but we can expect a lot of breakthroughs next year.

Ron Hause, SVP, head of AI, Shape Therapeutics

Today, many drugs and gene therapies are prohibitively expensive. Generative AI-enabled drug discovery and design—as well as innovations in manufacturing and drug delivery—will change that. Major breakthroughs for patient health are just around the corner.

Cameron Adams, cofounder and chief product officer, Canva

Single-function AI tools like Midjourney helped to bring a focus to generative AI, but in the year ahead, the technology will only truly bridge the gap to the masses via tools that are integrated into their actual workflows. This won’t just change the way that people create or edit images, but also the way they work—helping them to save hours of time with AI workflows that eliminate mundane tasks. It’ll enable work they mightn’t have even attempted before.

Roger Thornton, cofounder and general partner, Ballistic Ventures

Product managers are using LLMs to create working prototypes of the functionality they need engineering to implement, which challenges the very nature of how we develop software. In many cases, the code handed over to engineering is very close to commercial release. This has enormous implications to the way we structure software teams and may very well usher in the ability for domain experts to go from concept to code without the need for large engineering teams. 

Henrique Dubugras, founder and co-CEO, Brex 

As AI tools evolve, they can act as the silent assistant that helps bridge the gap such that a non-finance employee who’s making a purchase gets assistance to do what the finance person would want: Spend within budget while documenting and categorizing it properly. It’s this invisible help that actually will be the next platform shift. Particularly for finance and accounting teams, next year I think we’ll see a meaningful progression of AI’s applications that will enable them to focus on more strategic and proactive work, reducing repetitive data entry and analysis tasks. 

Roberto Masiero, SVP of innovation, ADP 

A generative AI tool could tell an HR professional that an employee hasn’t taken a vacation recently and might suggest reaching out to the person about taking some time off to avoid burnout. Another example: What if someone recently got married or had a baby? The generative AI tool could alert an HR pro that it might be time to resend benefits information to that employee. Human-sensitive nudges help people through the most important transactions of life and can create a happier experience for employees.

Victoria Espinel, president, BSA (Business Software Alliance)

If the past year was about building understanding of AI, then the year to come will be about putting to work some of the unique capabilities of generative AI. But we need thoughtful, globally consistent rules that work to reduce risks to build trust in AI. If we want businesses and consumers to benefit from responsible AI in the next year, governments need to act.

Chris Bedi, chief digital information officer, ServiceNow

Generative AI will . . . affect employee expectations for the technology they use at work, becoming table stakes for talent retention. If we don’t provide employees with GenAI solutions, I feel like it is asking them to use a typewriter when word processors are available. 

Robert Blumofe, CTO and EVP, Akamai Technologies

Right now, many applications are simple productivity enhancers to help employees, students, musicians, developers, and more perform tasks more efficiently and at a quicker speed. But as AI is integrated with other tools—for example, retrieval of company-specific data or online services, such as weather forecasts—and adjusted to serve various industries, we will start to see really interesting use cases emerge. 

Michelle Taite, CMO, Intuit Mailchimp

The biggest benefit I see to adopting generative AI right now is leveraging good data to create and scale personalized experiences. Generative AI’s ability to analyze vast amounts of individual customer data points and create individualized content won’t just benefit larger brands and enterprise organizations, either. The simplistic nature of generative AI has the power to act as an equalizer for small and mid-size businesses.

Chris Helsel, SVP, global operations, CTO, Goodyear Tire & Rubber Company

We can use [AI] as a tool to drive more efficiency within our organization’s product development, synthesizing decades of testing data, and enhancing our ability to forecast supply and demand planning. We already use AI to proactively predict tire service and leak protection based on billions of sets of historic data that can help reduce downtime for fleets, significantly helping our customers be more efficient.

Adam Williams, VP, product, global platforms, Iron Mountain

One of the biggest pain points we hear from customers is that they can’t find the information they’re looking for—and we’re excited about how generative AI can play a role in solving that in the coming year. What if you could ask your documents, your records, or your company data a question? For example, whether a specific document is signed? Or how many citizens born in a specific country are leveraging a specific service? Or the length of time a task takes at each stage of the supply chain?

Ding’An Fei, chairman, Investing.com 

For consumers, the multimodal chat apps will combine the utility of Wikipedia, search, voice-operated personal assistant with vastly intuitive multi-turn interface, and its experience will improve dramatically. Foundational model supercharged consumer applications in vertical areas like social, media, education, finance, entertainment, and others will also be widely adopted. These will come from both incumbent companies and startups.

Jun Hong Heng, founder & CIO, Crescent Cove Advisors 

We believe that generative AI tools are set to be a visionary force in various fields and we view the productivity gains, eventually, could be as impactful as the widespread electrification in the 19th and early 20th centuries. Some of the transformation might be gradual over a few years, but users of generative AI tools are already seeing productivity gains.

Eliot Andres, cofounder, PhotoRoom

We’re seeing that AI in photo-editing tools is helping remove friction in the creative process for photography professionals and small businesses in e-commerce and retail. As the labor-intensive side of photo-editing is automated by AI, the role of the photographer is shifting the creative side of photography as an art form: the style, the tone, and the graphic elements of an image. The opportunity with AI in photo editing is to use incredibly complex and sophisticated technology to make the act of creating and editing photos feel easier and more intuitive than ever before.

Steve Sewell, CEO, Builder.io

The transformative aspect of generative AI in today’s business landscape is its integration into broader tool chains. The combination of large language models with targeted, specialized models is where we are witnessing real, tangible progress.

Teri Ellison, chief human resources officer, SHL

AI tools will revolutionize the role of HR professionals. We’re already seeing the benefits of using this technology to automate some of the day-to-day HR activities and administrative tasks; for example, using generative AI to do the first draft of a job description or company-owned bots responding to basic employee questions and requests. Finding ways to use tech to support repeatable tasks is key for freeing up time and resources to allow people to focus on higher value work.

Vikram Chatterji, cofounder and CEO, Galileo (former product lead at Google AI)
The next year of ChatGPT and Midjourney will likely usher in a proliferation of business apps—a “custom GPT” for every function within an organization that deals with repetitive tasks, across finance, legal teams, and more. OpenAIs GPTs “App Store,” where folks don’t even need to know how to code to create personalized GPTs, was a big leap forward in this direction.

Florian Douetteau, CEO, Dataiku 

Generative AI will enable firms to integrate and analyze both private and public financial information on another scale. AI tools will synthesize data from earnings calls and comprehensive reports, providing a deeper understanding of company and market health. In scientific research, next year will bring a leap in generative AI assistance. Researchers will have sophisticated AI tools at their disposal that can compare their work against others around the world, predicting future research trajectories and identifying unexplored areas that are ripe for discovery.