AI Skills You Need to Propel Your Digital Marketing Agency to the Future

Chances are, you used AI today in your everyday life or workflows. AI has become ingrained in common tasks. If you checked social media, ordered something off Amazon, or watched Netflix, you were involved in a process with built-in AI.

With such technology becoming a part of day-to-day living and work, AI skills are becoming more important for digital marketing marketing agencies. 

The right AI skills let you position your agency as a leader and innovator, helping clients manage marketing in a world that is tech-heavy. Discover eight AI skills that can help your agency grow in the future below. 

1. Prompt Engineering

What Is It?

Prompts are the inputs fed to AI models that generate outputs. For example, if you ask ChatGPT a question, that’s a prompt that it then answers. 

Prompt engineering involves designing and refining the input to get a more desired output. For instance, if you want AI to generate viable product descriptions for a client, you must work to create specific prompts with the right information to ensure that the outputs are accurate and adhere to client style requirements.

The goal is typically not to get publish-ready content from AI but to minimize the time you have to spend humanizing AI content to make the output ready. 

Why Is It Important?

The compound annual growth rate (CAGR) for the prompt engineering market is expected to grow at the astounding rate of 32.8 percent from 2024 to 2030 (Grand View Research), making this one of the top growing skills for AI processes. It’s important because perfecting prompts is currently the best way to ensure optimal outputs from AI models. 

2. Understanding of LLMs (Large Language Models)

What Is It?

Large Language Models are complex AI systems that can understand human language and generate responses to inputs as a human would. They work by analyzing enormous amounts of existing text data and using that information to mimic the nuances of human language. 

Why Is It Important?

The CAGR for the LLM market is even more impressive than the CAGR for prompt engineering. Estimates put growth at 79.80 percent through 2030 (Springs). LLMs can be useful in conducting research and generating content drafts for email, blog posts, social marketing campaigns, and PPC ads.

For digital agencies, LLMs are positioned to drive content scale, as they help human teams create more content in less time.

3. Understanding of NLP (Natural Language Processing)

What Is It?

Natural Language Processing is a branch of AI that focuses on creating artificial human language responses. This is the technology that helps drive LLM functionality, but it’s also critical to a variety of other AI processes.

For instance, NLP tools can ingest large amounts of text and transform that data into summaries or actionable insights for marketing teams. 

Why Is It Important?

For marketing professionals, NLP technology can be a game changer in growth and the ability to serve many clients without adding human resources. It can help you extract actionable data from customer emails, social media posts, online reviews, and other sources.

Teams leverage this technology to improve customer experiences, optimize marketing campaigns, and make business decisions about services or products. 

Natural Language Processing is of growing importance to businesses in all sectors. Some sectors holding the highest market share in NLP include business and legal services, media and entertainment, energy, healthcare, finance, security, transportation, and retail (Market.us Scoop).

4. Software Integration Skills

What Is It?

Whether you’re starting an agency with no experience or working as an established expert with new clients, chances are that you’ll face processes that involve multiple apps or software. Software integration skills help you ensure disparate tools work well together, reducing errors or duplicate work.

For marketing agencies, the ability to integrate customer relationship management tools, marketing automation workflows, and content management systems is critical. 

Why Is It Important?

More than 80 percent of businesses say integrations are important to customers or clients (Partner Fleet), making this more than a critical artificial intelligence skill. It’s a tech skill you need in your agency, especially if you’re branding yourself as a vendor with white label software or as a specialist in marketing integration. 

Marketing is a tech-heavy industry today, and your clients may be looking for help streamlining these AI and technology processes as much as they are looking for assistance with compelling copy or ad campaigns that perform. While you don’t necessarily need in-house coding and dev skills, it’s critical that your team understands the big picture of AI integration and how various systems work together to create a functional marketing ecosystem. 

5. Understanding of Python

What Is It?

Python is a programming language that has many applications, including software and web development. It’s also important in machine learning processes and data science. At the same time, Python tends to be easier to learn than other programming languages, making it suitable for those just entering this niche and for non-development professionals that want access to some coding capability. 

Why Is It Important?

Despite being around for a long time in “tech years,” Python is still a major player in coding, development, and data analytics. According to a GitHub survey, Python use grew by 22 percent from 2021 to 2022 (GitHub). It continues to grow thanks in part to being a versatile AI skill. 

Marketing teams can use Python to:

• Develop websites. By pairing Python with the right frameworks, you can use it to quickly build custom client websites. You can use AI to help expedite code, creating or updating sites with minimal coding resources. 

• Develop software and apps. Marketing agencies can create or integrate software and apps for clients or their own processes with help from Python.

• Build or train machine learning models. Python can be used when training LLMs and other machine-learning models, helping to ensure accurate and targeted outputs.

• Analyze data. When you pair Python with libraries like Pandas, you can use it to conduct data analysis, helping to produce insights for better marketing decision-making. 

6. Tech Stack Consultation Skills

What Is It?

Tech stack consultation is the process of advising clients about what combination of software and technology tools will result in the best outcomes given their business goals, budgets, and other factors. 

Why Is It Important?

If you’re looking for start up ideas, offering tech stack consulting services may be a good one—on average, mid-market companies are using more than 180 apps in their tech stacks (Growth Natives).

Small and mid-size businesses are often overwhelmed with their tech stacks and may appreciate help in choosing the right tools and integrating them in a way that supports lead generating and other marketing performance. 

7. Knowledge of Data Technologies

What Is It?

Data technologies can range from basic spreadsheets and databases to advanced SQL reporting, data visualization, and big data platforms. AI tools can be critical to success with any sort of data technology today due in part to the sheer amount of data inherent in most processes.

This is certainly true in marketing, where data comes from disparate sources, including social media, email, CRM systems, and websites. 

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Why Is It Important?

In-depth knowledge of data technologies empowers marketing teams to analyze data and leverage it for strategic decision-making and greater success. Data technologies allow marketers to identify trends and gather important insights that help them craft better campaigns and drive increasing ROI. 

8. Data Analysis and Management

What Is It?

Data analysis and management are AI skills that stack on top of data technologies knowledge. These are the practical skills that allow agencies and marketing teams to take the data that comes from the skill above and apply it to real-world, practical scenarios.

Why Is It Important?

Obviously, AI data analysis skills help teams turn enormous amounts of raw data into actionable insights. For example, you may use these tools to figure out when the best time to send emails are for enhanced open and click-through rates. You can also leverage AI reporting to automate dashboard management, ensuring you have real-time access to key performance indicators about your marketing campaigns. 

However, these tools are important in other areas of business and marketing. For instance, consider a scenario where a client wants to make money with AI art. AI image tools create based on huge banks of data. With the right AI data analysis and management skills, you can begin to understand the relationship between the raw data, the prompt, and the AI image output. That lets you make changes to the data itself and not just the prompt, tweaking outputs to ensure better performance.