Artificial intelligence is creating new career paths, and two roles often in the spotlight are the AI consultant and the prompt engineer. Both jobs involve working with AI, but they differ greatly in focus and required skills.
An AI consultant helps businesses strategize and implement AI solutions, acting as a bridge between cutting-edge technology and real-world business needs. A prompt engineer, on the other hand, specializes in crafting effective inputs (prompts) for AI models, particularly generative AI like ChatGPT, to produce desired outcomes.
If you’re exploring AI careers, you might wonder which path is right for you. In this article, we’ll draw on over a decade of experience and insights from Refonte Learning to compare these roles side by side – from day-to-day responsibilities and skill sets to job prospects and future trends. By understanding the differences and opportunities of AI consultants vs. prompt engineers, you can make an informed decision about which career aligns best with your interests and the evolving AI industry.
AI Consultant: Role and Responsibilities
An AI consultant is a professional who advises organizations on how to leverage artificial intelligence effectively. They work closely with businesses to identify use cases for AI, choose appropriate tools, and ensure AI projects align with strategic goals. In essence, an AI consultant bridges the gap between a company’s business objectives and the complex world of AI technology.
For example, an AI consultant might help a retail chain deploy machine learning for demand forecasting, or guide a bank in implementing an AI-driven fraud detection system.
AI consultants typically handle a broad range of responsibilities. They may assess a client’s needs, determining whether AI can solve particular problems and which AI techniques are suitable. They provide AI strategy – selecting high-impact use cases, outlining project roadmaps, and setting success metrics.
Implementation is also key: while consultants might not always code solutions themselves, they must understand technologies (like machine learning, NLP, or computer vision) well enough to recommend the right approach and oversee technical teams.
Crucially, an AI consultant focuses on driving business value. Their recommendations center on improving performance or efficiency for the client (e.g. automating a process to save costs or using AI insights to increase revenue) in data. They often remain involved through deployment and evaluation, ensuring that the AI solutions deliver measurable benefits.
Strong communication and project management skills are vital in this role. AI consultants spend a lot of time with non-technical stakeholders – executives, managers, or clients from various industries. They must translate technical jargon into clear business terms and manage expectations.
In addition, they keep up with the fast-moving AI landscape. A consultant needs to know the latest AI tools and trends (from new machine learning algorithms to cloud AI services) to provide up-to-date advice. It’s a role that combines technical know-how with business acumen, and it’s deeply rooted in problem-solving and strategic thinking.
Prompt Engineer: Role and Responsibilities
A prompt engineer is a newer role that emerged with the popularity of generative AI models (like GPT-3, GPT-4, DALL-E, etc.). Prompt engineers specialize in designing and refining the textual (or other modality) prompts that instruct these AI models to produce useful outputs. In other words, they figure out the right way to “ask” the AI to get the desired responds.
For example, a prompt engineer might work on a chatbot project, crafting prompts that guide the AI to answer customer questions accurately and in a friendly tone. Or they might develop prompt templates for an image generation AI to create art in a specific style.
The prompt engineer’s daily work involves a lot of experimentation. They write prompts, run them through the AI model, and observe the results. If the output isn’t as expected, they tweak the prompt wording, add context, or impose constraints, and test again.
This iterative process requires understanding how the AI model interprets language. Skills in linguistics or psychology can be handy, as prompt engineers must anticipate how phrasing, syntax, or even punctuation can influence an AI’s response. They also often create guidelines for others to use the AI system – for instance, documenting which prompts yield the best outcomes for certain tasks.
Despite not always needing deep coding skills, prompt engineers benefit from a bit of technical background. They may use scripting to automate prompt testing or have to integrate prompts into a larger software workflow. Understanding the basics of how large language models work (and their limitations) is important so they can design prompts that avoid known pitfalls (like biased or irrelevant outputs).
One key aspect of prompt engineering is ensuring the AI output aligns with business goals or user needs. This means prompt engineers often collaborate with product managers, content experts, or domain specialists. For instance, at a company using AI to generate marketing copy, a prompt engineer would work with marketers to understand the brand voice and then craft prompts that make the AI produce text matching that voice.
It’s worth noting that prompt engineering as a distinct career rose quickly and is evolving just as fast. In early days, some prompt engineers commanded extremely high salaries (reports of up to $375,000 a year were noted for a prompt engineer role), highlighting the hype around this skill. However, as we’ll discuss, the landscape for this role is shifting.
Skills and Tools Comparison
Technical Skills: AI consultants require a broad understanding of AI and machine learning techniques, but they don’t necessarily code models from scratch daily. Instead, they need to know enough to identify what solution fits a problem – for example, recognizing when a simple regression will do versus when to deploy a deep learning model.
They should be familiar with data analysis, model evaluation, and possibly tools like Python, R, or SQL to analyze data. Prompt engineers, in contrast, need depth in understanding AI model behavior, particularly large language models. They must have excellent command of language and an analytical mindset to tune prompts.
While not always required to code, prompt engineers do well if they know some scripting (Python for calling APIs or analyzing outputs) and version control to manage prompt libraries. Both roles benefit from knowledge of popular AI platforms – an AI consultant might use cloud AI services (like AWS AI or Azure Cognitive Services) to implement solutions, while a prompt engineer might use interfaces or libraries from OpenAI or Hugging Face to test prompts.
Soft Skills: Communication is a critical skill for both careers, but in different ways. AI consultants need strong client-facing communication; they often present proposals, write reports, and train client teams.
They also need project management and the ability to lead cross-functional teams. Prompt engineers need a mix of creativity and precision in communication. Their “audience” is the AI model – so they have to communicate instructions to a non-human intelligence effectively. This requires creativity (to come up with novel ways to ask a question) and attention to detail.
Collaboration skills are important too: prompt engineers often act as a liaison between the AI model and the team using it, translating requirements into effective prompts and explaining AI outputs to colleagues.
Tools: AI consultants often use business and data analysis tools (from presentation software to notebook environments) to demonstrate AI concepts to stakeholders. Prompt engineers primarily work within AI model interfaces or playgrounds (e.g., OpenAI’s testing environment) to iterate on prompts. Both roles require comfort with learning new tools quickly, as AI technology evolves.
Career Outlook and Industry Trends
When comparing career prospects, it’s important to look at how each role fits into the evolving AI landscape. AI consultants have a role that aligns with the long-term needs of businesses.
As more companies plan to integrate AI, the need for strategists who can guide AI adoption remains strong. Many businesses lack in-house AI experts, so consultants will continue to be in demand globally. Companies will also need professionals who can craft AI strategies and ensure projects deliver value (including addressing AI ethics and compliance).
By 2025, prompt engineering as a standalone job title has largely disappeared – it’s now considered an embedded skill within other AI roles. Companies have found it more practical to require prompt crafting ability in roles like ML engineer or AI specialist, rather than hire dedicated prompt engineers. Some organizations even use AI tools to generate prompts, reducing the need for human specialists.
However, prompt engineering remains a valuable skill – it has shifted from a niche job to a core competency expected of AI professionals. Future AI roles (even AI consultant positions) will likely list prompt engineering as a desired skill, even if it’s not a job title on its own.
For career stability, AI consulting is a more established path (consulting as a profession isn’t going away). Prompt engineering expertise, being newer, is best combined with broader AI skills for long-term success.
Choosing the Right Path for You
Deciding between being an AI consultant or a prompt engineer depends on your interests, background, and career goals. Here are a few considerations to help you choose:
1. Interests: Do you prefer business strategy or hands-on tech work? If you like tackling organizational problems and communicating with clients, AI consulting may suit you. If you enjoy experimenting directly with AI models to see what makes them tick, you might prefer prompt engineering.
2. Skill Development: AI consulting helps you build project management and strategic planning abilities, combining technical and business knowledge. Prompt engineering, on the other hand, will sharpen your creative communication skills and your insight into how AI models respond. If you’re looking to train for either route, Refonte Learning has options – from comprehensive AI courses for future consultants to a dedicated Prompt Engineering Program for those focusing on that niche.
3. Job Market and Future: AI consultant jobs offer a more stable, long-term career path – companies around the world consistently hire for these roles. Prompt engineer positions are more niche and may not remain separate jobs indefinitely. If you lean toward prompt engineering, plan to broaden your skill set over time (e.g., adding software development or data science skills) to keep your career options open. On the other hand, having prompt engineering expertise can make you stand out when pursuing roles like AI consultant or AI developer.
Ultimately, remember that these paths are not mutually exclusive. You might start as a prompt engineer and later incorporate those skills into an AI consulting career. Or you might be an AI consultant who develops prompt engineering expertise as part of your toolkit. Both roles revolve around making AI useful for people – either by shaping strategy or by fine-tuning how we communicate with AI.
Refonte Learning emphasizes a comprehensive learning approach: build a strong foundation in AI fundamentals, and then specialize where your passion lies. Whether you choose the breadth of consulting or the depth of prompt engineering, staying curious and adaptable will ensure you remain relevant in the fast-evolving AI field.
Actionable Tips for Decision-Making
Assess Your Strengths: Are you more business-oriented or technically creative? If you enjoy client interaction and high-level planning, lean towards AI consulting. If you excel at crafting words and experimenting with AI outputs, prompt engineering might be a fit.
Try Mini-Projects: Experiment with both areas on a small scale. For instance, help a local business brainstorm an AI solution (consulting experience) and also play with a public AI model (like GPT-4) to practice prompt engineering. See which activity you find more engaging.
Build Core AI Knowledge: No matter the path, ensure you understand AI fundamentals. Knowledge of how models work will make you a better consultant and a better prompt engineer. Consider taking a foundational AI course through Refonte Learning to solidify this base.
Stay Adaptable: The AI field changes rapidly. If you go the prompt engineer route, keep an eye on emerging tools and be ready to expand your skill set (perhaps into AI development or data science). If you go into consulting, stay updated on the latest AI capabilities (so you can advise clients effectively). Continuous learning is key in both careers.
Frequently Asked Questions (FAQs)
Q: What does an AI consultant do, in simple terms?
A: An AI consultant helps businesses figure out how to use artificial intelligence to meet their goals. They evaluate a company’s needs, recommend AI solutions (like which AI software or model to use), and often help manage the implementation of those solutions. Think of them as AI strategy advisors – they make sure a company is doing the “right” AI projects in the “right” way to get results.
Q: What does a prompt engineer do?
A: A prompt engineer focuses on interacting with AI models (especially large language models like GPT) by crafting prompts – the instructions or questions given to the AI. Their goal is to get the AI to produce useful, accurate, and relevant outputs. It’s a role that requires understanding how the AI responds to different phrasing and providing the right context in the prompts.
Q: Do I need coding skills to be an AI consultant or prompt engineer?
A: Not necessarily. An AI consultant benefits from understanding code and data, but can often rely on technical teams for implementation. A prompt engineer can start with no coding (using AI tools through simple interfaces), but learning some programming will greatly expand your capabilities and career flexibility in both roles.
Conclusion
Both AI consultants and prompt engineers offer distinct ways to work with artificial intelligence. Your decision comes down to whether you prefer addressing business challenges with AI solutions or interacting directly with AI models to refine their outputs. The encouraging news is that these skill sets are complementary – many professionals blend strategic and hands-on expertise as the industry evolves.
Regardless of the path you choose, focus on building a strong foundation in AI fundamentals and commit to continuous learning. At Refonte Learning, we provide training for both tracks, because the future of AI careers will require a mix of strategic insight and practical skills. Stay adaptable and curious. With the right skill set and mindset, you can thrive as an AI consultant, a prompt engineer, or even a combination of both.