AI promises transformational benefits for B2B marketing, yet many teams struggle with adoption. Successfully integrating AI into your operations doesn’t just depend on technology – it revolves around three core pillars: People, Processes, and Procurement.
People: Closing the Skills Gap
The journey to effective AI adoption starts with your team. The skills needed from your everyday marketeer are rapidly evolving, with successful teams adding AI prompt engineering to marketing automation. Marketing and Revenue Operations teams should aim to have at least 20% of their teams dedicated to these skilled areas to stay competitive.
Beyond training existing talent, AI also creates entirely new roles, such as Automation Strategists, Prompt Engineers, AI Content QA Specialists, and Data-to-Insight Translators. Forward-looking companies are actively hiring and nurturing these roles to transform data into impactful strategies.
It’s not to overlook AI as a crucial part of a person’s role. Integrating AI tools directly into the everyday function of their job, rather than on isolated or ad hoc use, is key for people to adopt those core AI skills. Encourage innovation and the development of new skills, and create an environment that rewards experimentation and continuous learning.
In their article, How AI Can Help You Stand Out as an Employee Advocate, B2B social media management platform Oktopost, discusses how AI tools can assist employees in staying updated with industry trends, identifying content gaps, and generating relevant, high-quality posts. This empowers individuals to develop critical digital skills such as content creation, industry analysis, and thought leadership—capabilities that are increasingly important in AI-enabled workplaces.
Processes: Building Agile and Integrated Workflows
Effective AI adoption requires modernizing workflows and clarifying data ownership. Clear data governance ensures quality, compliance, and facilitates better decision-making when integrating AI into your operations.
Start by mapping out your existing technology platforms and understanding how data flows between systems like your marketing automation tools such as Adobe’s Marketo Engage, CRM (e.g., Salesforce), and ERP systems. Identify inefficiencies and manual processes, considering where AI or AI Agents can do the heavy lifting or take over time-intensive, repetitive tasks. Consider the following examples:
Lead Routing and Enrichment with AI Agents
Map how new leads flow from Marketo Engage to Salesforce. If lead assignment is manual or based on static rules, introduce an AI agent to analyze behavioral data and route leads dynamically based on likelihood to convert, account fit, or sales readiness. This reduces manual effort and increases speed to lead.
Renewal Risk Identification Using Adobe Real-Time CDP and Salesforce
Integrate Adobe Real-Time CDP with Salesforce to unify customer data from web behaviour, support interactions, and product usage. Use AI models within Adobe’s Intelligent Services to score renewal risk based on engagement decline, sentiment signals, or drop-offs in product usage. Sync these insights into Salesforce to alert account managers to at-risk customers and trigger tailored retention campaigns via Marketo Engage.
Adopting agile methodologies will allow your team to rapidly test, iterate, and implement new AI or Agentic-supported processes. Regularly re-visit your workflow map and optimize processes in it to maintain agility and ensure continuous improvement. In time you will see go-to-market motions take less time and become easier to execute.
Procurement: Selecting the Right AI Tools
Choosing the right AI technology involves balancing functionality with scalability. Ensure any AI solution you procure addresses immediate needs while scaling effectively with your future business growth.
Evaluate potential AI tools on functionality, ease of integration, support, and total cost of ownership. Carefully consider if the tool adds value to your current processes or if it introduces unnecessary complexity, or worse future technical debt. It’s vital to weigh the trade-offs between building internal solutions and buying external AI tools. Typically, external solutions offer quicker implementation, lower ongoing maintenance, and less internal resource dependency.
Consider these key factors when selecting AI platforms:
- Functionality and scalability – will it meet your future needs or scale with your growing business?
- Ease of integration and support availability – can the platform easily connect to existing tools with reliable support, clear documentation, and an active partner network?
- Total cost of ownership and resource investment – include licences, setup, training, admin time, and any extra costs for AI or specialist support.
- Long-term viability and ability to evolve alongside your business – does the platform have a strong roadmap and regular updates to keep pace with your needs?
If you’re asking yourself How do I bring my 3 Ps together into an AI strategy for marketing?
It’s best to start by ensuring your team has the necessary skills and clear processes to guide AI adoption. Then, select technology that truly fits your operational needs. With these three pillars, you’re setting your organization up for sustainable AI-driven success.
Want some additional support to guide you through your AI journey? We’d love to help.
For more insights on strategically integrating AI into your marketing, download our practical guide: AI for Marketing Leaders