AI for Marketing Consultants [Strategies & Tools]

AI is changing how marketing consultants work with clients.

The numbers tell the story. AI marketing hit $47.32 billion in 2024 and will likely exceed $107 billion by 2028. Right now, 88% of marketers use AI daily, and 92% of businesses plan to invest in it soon.

If you're not using AI yet, you're already behind.

I created this guide to help you catch up and get ahead. You'll learn how to use AI to deliver better results for your clients, automate time-consuming tasks, and build smarter marketing strategies.

Here's what I'll cover:

→ What AI marketing actually means and why it matters now
→ Practical ways to use AI for data analysis, content creation, and personalization
→ How to choose and implement the right AI tools for your clients
→ Steps to build AI into your consulting services and price them right
→ What's coming next in AI marketing

Let's start with the basics.

What is AI Marketing?

AI marketing means using smart technology to handle tasks that normally need human thinking. It analyzes data, spots patterns, and makes decisions faster than any person could.

For marketing consultants, AI acts like a powerful assistant. It can predict which leads will convert, write email drafts, or tell you the best time to post on social media.

The main types: GenAI, Machine Learning, and NLP

Three types matter most:

→ Generative AI (GenAI) creates new content—blog posts, ad copy, images
→ Machine Learning (ML) finds patterns in customer data to predict behavior
→ Natural Language Processing (NLP) understands and generates human language for chatbots and sentiment analysis

Try DFIRST to Create Marketing Campaign Faster

DFIRST is a platform where you connect AI tools on a canvas to create marketing campaigns faster. Instead of juggling multiple apps and manual work, you build workflows that handle everything from research to final ads.

→ The Canvas: Build campaigns by connecting simple nodes on a canvas. Draw lines to link research, writing, and image steps. The data moves automatically, so you don't copy-paste.

→ Research Built In: The platform checks multiple sources—competitor sites, social media, papers. Set up a research node to pull market data right into your content flow.

→ Creating Marketing Assets: Text nodes write ads and posts. Image nodes use tools like DALL-E to make visuals. The system keeps track, so your images always match your writing.

→ 50+ AI Model: You can use models like GPT-4, Claude, and Gemini. The platform chooses the best one for each task, or you can pick yourself. Pro users get faster, newer models.

→ Your Data Room: Upload your brand guides and old files. The AI learns from these documents to match your company's voice. Your private data is never used to train the models.

→ Working Space: Every campaign gets a dedicated whiteboard. Start with a template or ask the AI to build a workflow for you. Save the best ones to use again later.

For agencies doing client work, this matters. You can cut production time from weeks to hours while keeping everything consistent. Pricing: Free 80 tokens daily. Starter: $39/month. Pro: $199/month. 

Generate your first flow for free - no credit card required.

How AI is Changing the Job for Consultants

AI handles the repetitive work—data analysis, report generation, content drafts. This frees you up for strategy and client relationships.

You're shifting from doing tasks to managing AI tools that do them. Your value now comes from knowing which tools to use, how to interpret AI insights, and turning data into strategy.

Clients expect AI-driven recommendations. Those who adapt stay competitive.

Why AI Isn't Optional Anymore

AI helps marketing consultants deliver measurably better results while cutting execution time in half. According to McKinsey's 2025 State of AI report, companies using AI in marketing saw a 30% increase in customer engagement and a 25% reduction in campaign costs.

The data shows that 72% of high-performing marketing teams now use AI tools daily, compared to just 18% of underperforming teams.

AI has become essential because it:

• Helps clients get better results, faster – AI analyzes campaign performance in real-time and automatically adjusts targeting, messaging, and budgets to maximize ROI without manual testing.

• Makes smarter decisions with data – Machine learning spots patterns in customer behavior that humans miss, turning raw data into actionable insights within minutes instead of weeks.

• Truly personalizes at scale – AI creates individualized content and recommendations for thousands of customers simultaneously, something impossible with manual segmentation.

• Gives your clients an edge – Businesses using AI marketing tools outpace competitors who rely solely on traditional methods, capturing market share through faster, more precise execution.

How to Actually Use AI

Applying AI to marketing consulting means turning data into action, automating repetitive work, and delivering personalized experiences at scale. The tools exist—your job is knowing where they fit best.

Here's what AI can do for your clients:

Finding Answers in Your Data

AI helps marketing consultants extract insights from client data faster and more accurately than manual analysis. This means better predictions, real-time reporting, and smarter budget allocation.

• Predicting customer behavior and value: Machine Learning models analyze past purchase behavior, browsing patterns, and engagement metrics to forecast customer lifetime value (CLV) and churn risk. This helps prioritize high-value segments.

• Checking campaign results in real-time: AI-powered dashboards track KPIs across channels instantly, flagging underperforming campaigns and reallocating budgets without waiting for end-of-week reports.

• Seeing what people think about a brand: Natural Language Processing (NLP) scans social media mentions, reviews, and comments to gauge sentiment. You get a clear picture of brand perception without manual monitoring.

• Figuring out which touchpoints really work: Attribution models powered by AI analyze multi-channel journeys to identify which touchpoints drive conversions, moving beyond last-click attribution.

Pro Tip: Use predictive analytics to identify at-risk customers before they churn. Proactive retention campaigns are cheaper than acquisition.

Using AI for Market Research

Try marketing insights hub template prepared by DFIRST AI community

AI turns market research from a time-consuming task into a continuous process. You get fresher insights, faster competitor analysis, and more accurate customer personas.

• Keeping an eye on competitors: AI marketing research tools monitor competitor websites, ads, pricing changes, and social media activity. You spot strategic shifts early and adjust client strategies accordingly.

• Spotting market trends early: Machine Learning algorithms scan news, search trends, and social conversations to identify emerging opportunities before they become mainstream.

• Building better customer personas: AI analyzes behavioral data, survey responses, and CRM records to create detailed, data-backed personas. These go beyond demographics to include motivations, pain points, and purchase triggers.

Common Mistake: Relying only on historical data. Use AI to spot emerging segments, not just describe existing ones.

Creating Content and SEO with AI

Try content creation template prepared by DFIRST AI community

Generative AI speeds up content production and helps identify SEO opportunities. It won't replace your strategy, but it handles the heavy lifting. 

• Writing drafts (blogs, social posts, scripts): AI content marketing tools like ChatGPT and DFIRST generate first drafts based on prompts. You edit for tone, accuracy, and brand voice—saving hours per piece.  

• Using AI to improve SEO: AI platforms analyze top-ranking pages, suggest on-page optimizations, and identify technical SEO issues automatically.

• Grouping keywords and finding new topics: AI clusters related keywords by search intent and uncovers content gaps competitors haven't filled yet.

• Checking content and finding gaps: Content audits powered by AI compare your client's content library against competitor sites and search demand, highlighting missing topics or outdated posts.

Pro Tip: Use AI for research and drafts, but always add client-specific insights and examples. That's where real value lives.

Making Marketing More Personal with AI

Try personalised email campaign template prepared by DFIRST AI community

Personalization at scale is where AI delivers serious ROI. It tailors experiences to individual users without manual segmentation.

• Creating one-on-one marketing plans: AI builds dynamic customer profiles that update in real-time, triggering personalized offers based on behavior, not broad segments.

• Smarter email marketing: Predictive send-time optimization, subject line testing, and content recommendations happen automatically. Open rates and conversions improve without extra effort.

• Changing website content for each visitor: AI adjusts landing page headlines, CTAs, and product recommendations based on visitor source, past behavior, and predicted intent.

• Mapping out and improving the customer journey: AI identifies friction points by analyzing drop-off rates, session recordings, and heatmaps. You fix bottlenecks before they hurt conversions.

Pro Tip: Start with email personalization. It's easier to implement and delivers measurable results quickly.

AI in Advertising

Try ad creative generator prepared by DFIRST AI for free

AI manages ad campaigns with speed and precision humans can't match. It optimizes bids, tests creative, and targets audiences in real-time.

• Programmatic ads and auto-bidding: AI buys ad inventory and adjusts bids automatically based on conversion likelihood, maximizing ROI without constant manual tweaking.

• Creating ad copy and images: AI advertising tools such as DFIRST and Loveart produces multiple ad variations for A/B testing. Platforms like Meta's Advantage+ Creative generate headlines, descriptions, and image combinations.

• Using AI to manage ad budgets: Algorithms shift spend toward high-performing campaigns and pause underperformers, ensuring every dollar works harder.

• Better audience targeting: Machine Learning analyzes user behavior to build lookalike audiences and predict who's most likely to convert.

Common Mistake: Letting AI run ads with no strategy. Set clear goals and guardrails—AI optimizes, but you decide what success looks like.

Using AI to Automate Tasks

Try url based campaign builder by DFIRST AI for free

AI handles repetitive marketing tasks so consultants can focus on strategy and client relationships. Automation improves efficiency without adding headcount.

• Automating small, repetitive jobs: Scheduling social posts, tagging leads in CRMs, generating weekly reports—AI handles these without supervision.

• AI chatbots for customer service: Chatbots answer common questions 24/7, qualify leads, and escalate complex issues to humans. Response times drop, satisfaction rises.

• Scoring new leads automatically: Predictive lead scoring ranks prospects based on fit and behavior, so sales teams focus on the highest-quality opportunities first.

Pro Tip: Map out your most time-consuming tasks first. Automate those before adding new AI workflow tools.

Building a Marketing Strategy with AI

Try global strategy template prepared by DFIRST AI for free

Building an AI-powered marketing strategy means integrating AI tools into your client's existing framework to improve performance and efficiency. Start by identifying where AI can add the most value—whether in content creation, audience targeting, or campaign optimization. Map AI capabilities to specific business goals like increasing lead generation or improving customer retention.

• Adding AI to a client's main strategy: Integrate AI gradually into core marketing activities. Begin with low-risk areas like content scheduling or email personalization before moving to critical functions like budget allocation.

• Using AI for SWOT analysis: AI tools can analyze competitor data, market trends, and customer sentiment to build detailed SWOT analyses faster than manual research.

• Planning and testing campaigns before launch: Use predictive analytics to model campaign outcomes before spending budget. AI can simulate different scenarios and suggest the highest-performing approach.

Pro Tip: Always align AI initiatives with measurable KPIs from day one. This makes it easier to prove ROI to clients later.

How to Pick the Right AI Tools

Choosing the right AI tools for clients depends on their specific needs, budget, and existing tech stack.

Here's the process you can follow:

#1: Identify Tool Categories Needed

Different tool types (CRM, SEO, Ads)

Start by categorizing tools based on function. CRM platforms like HubSpot AI handle customer data and personalization. SEO tools like Clearscope optimize content for search. Ad platforms like Google Ads AI automate bidding and targeting.

Match tool types to client pain points—don't buy features they won't use.

#2: Evaluate Vendor Capabilities

A simple way to choose a vendor

Create a vendor scorecard with criteria like ease of integration, support quality, pricing model, and scalability. Test each platform with a free trial before committing.

Check customer reviews on G2 or Capterra for real-world feedback.

Common Mistake: Choosing tools based on features alone. Prioritize tools that integrate smoothly with your client's current systems to avoid data silos.

#3: Compare Popular Platforms

Comparing common tools (like Jasper or HubSpot AI)

DFIRST excels at content generation with templates for blogs and ads. HubSpot AI integrates content, CRM, and email automation in one platform. Semrush AI focuses on SEO research and competitor analysis.

Compare pricing, use cases, and learning curves to find the best fit.

#4: Decide - Build vs. Buy

Should you build your own tool or buy one?

Most consultants should buy existing tools. Building custom AI requires technical expertise, ongoing maintenance, and significant investment. Only consider building if your client has unique needs that no vendor solves, or if they have in-house development resources.

How to Set Up AI for Your Clients

Setting up AI tools for clients involves integrating new systems, preparing data, and training their team for smooth adoption.

Here's the process:

#1: Integrate with Existing Tech

Map out your client's current martech stack before adding AI. Check if new tools offer native integrations with platforms like Salesforce, WordPress, or Google Analytics.

Use middleware like Zapier or Make to connect tools that don't integrate directly. Test data flow between systems to avoid errors.

#2: Clean and Prepare Data

AI tools need clean, structured data to work properly. Audit your client's existing data for duplicates, errors, and missing fields.

Standardize formats for names, dates, and categories. Remove outdated or irrelevant records. This prep work directly impacts AI accuracy.

Pro Tip: Start with a data audit before implementing any AI tool. Poor data quality is the #1 reason AI projects fail.

#3: Create an Implementation Roadmap

Break implementation into phases. Start with one or two tools in a pilot program, measure results, then scale.

Define timelines, assign responsibilities, and set milestones for each phase. Include buffer time for troubleshooting and team training.

#4: Train the Client's Team

Create simple training guides and video walkthroughs for each tool. Run hands-on workshops where team members practice real tasks.

Assign an internal champion who can answer questions and encourage adoption. Schedule follow-up sessions to address challenges after the initial launch.

Talking to Clients and Showing Results

Communicating AI value to clients requires clear explanations, transparent reporting, and realistic expectations about outcomes.

Here's the process:

#1: Simplify AI Explanations

Avoid technical jargon when discussing AI with clients. Focus on business outcomes instead of algorithms. Use examples: "This tool analyzes past customer behavior to predict who's most likely to buy" instead of "This uses machine learning classification models."

Common Mistake: Overselling AI as magic. Always be honest about what AI can and cannot do to maintain trust.

#2: Build Transparent Dashboards

Create custom dashboards that show AI impact on key metrics like conversion rates, cost per lead, or content engagement. Use tools like Google Data Studio or Tableau to visualize before-and-after comparisons. Include annotations explaining which AI actions drove specific results.

#3: Set Realistic Expectations

Define success metrics before implementation. Clarify that AI improves over time as it learns from more data.

Set a realistic timeline for seeing results—typically 2-3 months for initial improvements. Document these expectations in your proposal.

#4: Structure Your Pricing

Consider these pricing models: 

• Monthly retainers for ongoing AI management

• Project-based fees for setup and integration

• Performance-based pricing tied to specific outcomes.

Factor in tool costs, training time, and ongoing optimization work. Be transparent about what's included in each pricing tier.

Keep Learning

Staying competitive as a marketing consultant means building new skills and keeping your team updated on AI developments.

Here's what you need to focus on:

The Data Skills Consultants Need Now

Marketing consultants need basic data literacy to work effectively with AI tools. Focus on understanding data analysis fundamentals, how to interpret AI outputs, and basic prompt engineering for generative AI tools.

You don't need to become a data scientist. Learn to read analytics dashboards, understand attribution models, and ask the right questions about data quality.

Pro Tip: Start with Google Analytics and your CRM reports. Practice explaining what the numbers mean in plain language to clients—this builds both your data skills and communication ability.

Good Courses and Resources for Learning

Several platforms offer practical AI marketing courses. LinkedIn Learning and Coursera provide marketing-specific AI courses that fit busy schedules.

• DFIRST in collaboration with SEMrush offers free AI certification courses focused on marketing applications. Google's AI Essentials course covers fundamentals in a few hours.

• Join marketing AI communities like the Marketing AI Institute or follow newsletters like "Be AI Optimistic" for weekly updates on new tools and techniques.

Common Mistake: Avoid courses that focus too heavily on technical AI development. Choose programs teaching AI application in marketing contexts instead.

Getting Your Team to Think AI-First

Building an AI-first mindset means making AI part of your default workflow, not an afterthought. Start by identifying repetitive tasks your team can automate or enhance with AI.

• Create a shared document where team members log AI tools they test and results they achieve. Schedule monthly sessions to demo new tools and share wins.

• Set a rule: before starting any project, ask "Can AI help here?" This simple question shifts thinking from manual execution to strategic AI application.

• Encourage experimentation by setting aside time for testing new tools without pressure for immediate ROI.

Using AI Responsibly

AI brings power—and responsibility. Marketing consultants must handle client data ethically and stay compliant with regulations.

Handling data privacy rules (like GDPR)

GDPR, CCPA, and similar laws require explicit consent before collecting personal data. When using AI tools, ensure they process data lawfully and store it securely. Always check vendor compliance certifications and audit data flows regularly. Document consent records and give customers easy opt-out options.

Checking for and fixing bias in AI

AI models learn from data—if that data reflects bias, your campaigns will too. Regularly test AI outputs across different demographics. If your ad targeting excludes certain groups unfairly, adjust your training data or algorithm parameters. Diverse teams catch bias better than homogenous ones.

Being open about how you use AI

Tell clients when AI creates content, scores leads, or personalizes messaging. Transparency builds trust and helps clients make informed decisions about their brand voice.

Setting your own rules for using AI safely

Create internal guidelines: when to use AI, what requires human review, and how to handle sensitive data. Train your team on these standards and update them as AI evolves.

What's Coming Next in AI

The AI landscape keeps changing fast. Here's what marketing consultants should watch for.

New AI tools on the way

Expect more specialized tools built for specific marketing tasks. AI platforms will get better at cross-channel campaign management, offering real-time optimization across all touchpoints at once.

Voice and visual search AI will become standard features in SEO tools. Emotion AI—which reads facial expressions and voice tone—will help brands understand customer reactions better.

How AI might change the consultant's job

Your role will shift from doing tasks to directing AI systems. You'll spend less time on execution and more on strategy and creative thinking. Consultants who combine AI knowledge with human insight will be most valuable. The focus will be on interpreting AI outputs, not creating content from scratch.

The rise of hyper-automation

Hyper-automation connects multiple AI tools to handle entire workflows without human input. Marketing campaigns will run end-to-end automatically—from research to content creation to performance optimization.

This means faster execution and lower costs for clients.

AI's role in Web3 and the metaverse

AI will power personalized experiences in virtual worlds. Think custom avatars, dynamic virtual storefronts, and AI-driven brand interactions in metaverse platforms. NFT marketing and blockchain-based loyalty programs will use AI for targeting and personalization.

It’s a Wrap

Using AI is all about connecting the dots, not just using separate tools. I covered how you can use it for everything from research to running ads—helping you get better results for your clients, faster.

The best way to do this is with a platform like DFIRST. You can build entire campaigns by connecting different AI tools on a visual canvas, without any manual work.

Generate your first flow for free - no credit card required.