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AI’s popularity is rapidly growing not only in the tech industry but every other one as well, as organizations quickly move to adopt the technology to streamline business processes.

A recent survey of senior IT professionals from Foundry found that AI spending is predicted to remain steady through the rest of 2025, with 61% of organizations stating they plan to increase spending, and only 1% saying they planned to decrease it. And a total of 88% said they’ve already invested or plan to invest in tools that help build AI capabilities internally.

Organizations are investing in tools to build AI capabilities with a focus on skills development and learning platforms (39%), data visualization and reporting (37%), data storage and management (37%), natural language processing (32%), and project management (31%). Employee productivity is also a significant driver of AI adoption, with 68% listing it as the top priority driving AI investments. Other reasons include improving customer service (55%), enabling innovation (54%), expanding revenue opportunities (47%), speed of development (44%), and need for real-time information (42%).

As this technology gains popularity, it’s increased the demand for relevant roles to help design, develop, implement, and maintain AI in the enterprise.

In addition, Foundry’s AI survey identified several roles that companies are looking to fill to help integrate AI in the workplace. Here are the top 11 roles companies are currently hiring for, or have plans to hire for, to directly address their emerging AI strategies.

Machine learning engineer

Machine learning (ML) engineers are tasked with transforming business needs into clearly scoped ML projects, along with guiding the design and implementation of ML solutions. This role is responsible for training, developing, deploying, scheduling, monitoring, and improving scalable ML solutions in the enterprise. It’s also a role that requires a wide range of skills including model architecture, data and ML pipeline creation, software development skills, experience with popular MLOps tools, and experience with tools like BERT, GPT, and RoBERTa, among others. The goal of a is to ultimately make ML more accessible across the organization so everyone can benefit from the technology. According to the survey, 20% of respondents say they’ve already hired ML engineers to support AI, while 55% say they have plans to hire for the role.

Deep learning engineer

Deep learning engineers are responsible for heading up the research, development, and maintenance of the algorithms that inform AI and ML systems, tools, and applications. , and vital to the development of AI tools and resources in the enterprise. This role is responsible for building and maintaining powerful AI algorithms, identifying data requirements, and finding better ways to automate processes in the business to improve performance. Technologies such as chatbots, virtual assistants, facial recognition, medical devices, and automated cars rely on deep learning to create effective products. As companies continue to embrace AI, deep learning engineers are critical for businesses that want to capitalize on AI and integrate it into business processes, services, and products. According to the survey, 15% of respondents say they’ve already hired deep learning engineers to support gen AI, while 54% say they have plans to hire for the role.

Prompt engineer

Prompt engineers are responsible for designing, optimizing, and structuring instructions for AI systems to produce specific text, images, code, and other outputs from gen AI models, such as ChatGPT. It’s a role that’s growing in demand across every industry as organizations embrace AI tools and look for professionals to make the most of their AI investments.

While AI tools make it easier to build and optimize software and service, they require specific input prompts to achieve desired outputs. Prompt engineers typically need experience and skills around AI research, software development, programming, Natural Language Processing (NLP), ML, and data handling and pre-processing skills. According to the survey, 15% of respondents say they’ve already hired prompt engineers to support gen AI, while 54% say they have plans to hire for the role.

Data scientist

As companies embrace AI, they need data scientists to help drive better insights from customer and business data using analytics and AI. For most companies, AI systems rely on large datasets, which require the expertise of data scientists to navigate them. Responsibilities include building predictive modeling solutions that address both client and business needs, implementing analytical models alongside other relevant teams, and helping the organization make the transition from traditional software to AI infused software. It’s a role that requires experience with natural language processing, coding languages, statistical models, and large language and gen AI models. According to the survey, 26% of respondents said they’ve hired data scientists to support gen AI, while 53% said they have plans to hire candidates.

AI researcher

AI is still new territory for businesses, and there’s a lot to discover, which is why they’re looking to hire AI researchers to help identify the best possible applications of AI within the business. AI researchers help develop new models and algorithms to improve the efficiency of gen AI tools and systems, and identify opportunities for how AI can be used to improve processes or achieve business needs. AI researchers need to understand data and automation infrastructure, ML models, AI tools and algorithms, data science, programming, and how to build AI models from scratch. According to the survey, 18% of respondents say they’ve already hired AI researchers to support gen AI, while 52% say they have plans to hire for the role.

Algorithm engineer

Algorithm engineers, sometimes referred to as algorithm developers, are tasked with building, creating, and implementing algorithms for software and computer systems to achieve specific tasks and business needs. The role of the algorithm engineer requires knowledge of programming languages, testing and debugging, documentation, and, of course, algorithm design. These engineers are responsible for solving complex computational problems in the organization, often working with large data sets to design intricate algorithms that address and solve business needs. Businesses rely on algorithm engineers to help navigate AI technology, relying on these experts to scale and deploy AI solutions, consider all the ethical and bias implications, and ensure they’re aligned with all compliance and regulatory requirements. According to the survey, 17% of respondents say they’ve already hired algorithm engineers to support gen AI, while 51% say they have plans to hire for the role.

AI chatbot developer

Chatbots are one of the earliest and most common uses of AI in a business setting; it’s very likely you’ve interacted with an AI chatbot at some point. AI chatbot developers help develop and build chatbot tools to direct customers to the right associates, connect users with important documentation, and alleviate some of the load on customer service representatives. With AI, chatbots are becoming even more sophisticated with the rise of services such as ChatGPT, Bard, Replika, Cleverbot, and others, which have shown to be powerful tools to businesses. Chatbot technology is in demand across every industry, and businesses are eager to hire AI chatbot developers to help build internal chatbot tools to streamline customer service, appointment scheduling, social media engagement, user support, and even marketing and promotions. It’s a role that requires skills and expertise around programming languages, AI/ML concepts and frameworks, and a strong grasp on NLP, as well as strong communication skills. According to the survey, 21% of respondents say they’ve already hired AI chatbot developers to support gen AI, while 44% say they have plans to hire for the role.

Chief AI officer

As AI establishes itself as a cornerstone of technology, the role of chief AI officer (CAIO) is becoming increasingly common to help oversee and manage the organization’s AI infrastructure. It’s a senior executive position designed to help guide organizations through the digital transformation of embracing AI, with deep technical knowledge and hands-on experience in the industry. This role requires a strong knowledge of AI ethics, governance and compliance, privacy, security, as well as the leadership and communication skills required to run a team of AI professionals. Organizations will continue to build AI tools and integrate AI into the workforce, making the role of CAIO increasingly important to help guide businesses through this monumental shift. According to the survey, 16% of respondents say they’ve already hired a CAIO to support gen AI, while 44% say they have plans to hire for the role.

Related reading:

• Making AI real: It takes a CAIO
• CAIOs are stepping out from the CIO’s shadow
• CDO and CAIO roles might have a built-in expiration date

AI writer

AI writers are tasked with creating written content using gen AI and then reviewing, editing, and reworking that content to quickly produce blog posts, articles, and social media updates, all faster than the average human. The role requires a strong understanding of SEO, prompt engineering, NLP, content management, data analysis, and knowledge of popular AI tools. You’ll also need a strong understanding and knowledge of copyright laws and ethical considerations around AI writing, which are still up for debate and evolving. According to the survey, 14% of respondents say they’ve already hired AI writers to support gen AI, while 44% say they have plans to hire for the role.

AI artist

Similar to AI writer, AI artists use AI to create artwork for companies including logos, branding, stock images, and other creative content for products, services, and marketing campaigns. It’s a role that requires creative experience combined with the technical knowledge of NLP, ML, AI, and prompt engineering. You’ll need to ensure the right images are created and then also have an eye and skill to edit and improve the AI outputs to ensure they accurately represent the brand. Much like AI writing, AI art is another contentious topic that draws criticism regarding the automation of art. Nevertheless, AI artist is an increasingly popular role as businesses embrace this implementation of AI to expedite advertising campaigns, streamline posting online content, and speed up delivery times for creative work. According to the survey, 10% of respondents say they’ve already hired AI artists to support gen AI, while 41% say they have plans to hire for the role.

Natural Language Processing engineer

NLP engineer is a vital role for embracing AI in any organization. AI relies heavily on NLP to improve communication and create chatbots and other AI services that need to communicate effectively with users, no matter the query. This role is responsible for training NLP systems, developing models, running experiments, identifying proper tools and algorithms, and performing regular maintenance and analysis of the models. Candidates typically have experience in big data, coding, model selection and customization, language modeling, language translation, and text summarization using NLP tools. NLP plays a big role in technologies such as text-to-speech (TTS) and speech-to-text (STT), chatbots and virtual assistants, and other AI tools designed to interact in real-time with users. According to the survey, 17% of respondents say they’ve already hired NLP engineers to support gen AI, while 18% say they have plans to hire for the role.