I developed this framework because I couldn’t find one that truly met my needs—so I built what I wished existed. It’s designed to help you and your team move from AI-curious to AI-confident. It outlines internal and external challenges, maps practical AI use cases across the marketing value chain, and introduces a maturity model spanning People, Processes, and Technology. It also includes a role-based growth framework that defines how AI-related skills and expectations evolve across different seniority levels–helping teams build clarity around development, responsibility, and impact
It was developed in collaboration with generative AI (ChatGPT), based on real-world insights gained through hands-on work with marketing teams. The structure, direction, and strategic thinking reflect the author’s experience, while AI was used to support ideation, drafting, and refinement under human guidance.
The Challenges Ahead: Why AI Adoption in Marketing Isn’t a Plug-and-Play Move
The rise of AI marks a fundamental inflection point for marketing teams across the world –redefining not just how we work, but what great marketing even looks like. Under mounting pressure to deliver more, faster, and with sharper personalization, marketers must now navigate a world where content is abundant, attention is scarce, and differentiation is harder than ever. Generative AI has shattered traditional production barriers, creating both a surge in possibility and a spike in risk.
It’s not just about getting a new tool, it’s a transformation of mindset, methods, and mandates. To thrive, marketing teams must evolve their skills, systems, and ethics—while confronting the external realities of how audiences discover, trust, and engage with brands in an AI-mediated world.
Those who adapt will amplify their impact. Those who don’t risk becoming invisible.
📘 How to Use This Framework
- Understand the Landscape Use the internal and external challenges sections to deepen your understanding of how AI is reshaping marketing.
- Identify Relevant Use Cases Explore the use case library to see where AI can support your strategy, planning, execution, and optimization efforts. Evaluate which use cases are applicable to your specific team, campaigns, or business context.
- Assess Team Readiness Refer to the maturity models under People, Processes, and Technology to evaluate where your team stands today—and what it would take to progress toward responsible, scalable, and strategic adoption.
- Guide Growth and Development Leverage the Marketer Growth Framework to align expectations across different seniority levels. It outlines how AI fluency and responsibilities should evolve from junior to lead roles.
- Foster Strategic Conversations Use the framework to spark cross-functional dialogue around ethics, tooling, governance, and creative standards—ensuring alignment as AI becomes a core part of marketing operations.
Internal Challenges (People, Processes, Technology)
These challenges relate to how marketing teams internally adopt, apply, and govern AI across people, processes, and technology. As AI tools become more accessible and expectations rise, many teams face uneven skill levels, unclear usage boundaries, and a growing tension between speed and quality.
| Challenge | Description | Impact |
|---|---|---|
| Skill disparity | Not all marketers are equally comfortable with AI tools, leading to uneven adoption. Also, marketers should be able to determine when the AI will have a positive (productivity) impact and when not. | Forces teams to rethink how they hire and assess talent, onboard employees, and deliver continuous training. |
| Quality risks | GenAI can generate fast, but not always well. Poorly curated output erodes brand credibility. | Forces marketers to define quality standards for different stages of the content lifecycle, and to reintroduce “human curation” as a necessary creative checkpoint. |
| Ethical concerns | Using GenAI without understanding its provenance (e.g., training on copyrighted or culturally sensitive material) can backfire. | Forces organizations to educate teams on responsible AI use and to build a shared understanding of where human sensitivity still matters—especially across generations and cultures. |
| Tool chaos | A growing stack of AI tools creates fragmentation and decision fatigue. | Forces leaders to centralize guidance, approve standard tools, and embed them into workflows so that AI doesn’t become a productivity tax. Beyond quantity, teams must also understand functional differences—some tools excel at research synthesis, others at language generation, visual prototyping, or data summarization. Knowing which AI to use when is as important as knowing how to use it. |
| Fear of irrelevance | For some, AI adoption feels like a threat to their creative identity or role. | Forces managers to create a psychologically safe environment for experimentation, where AI is framed as an enhancer—not a replacement—of human creativity. |
| Lack of governance | Without clear guidelines, AI use can spiral—internally and externally—into brand inconsistency or reputational risk. | Forces teams to document rules of engagement, approval flows, and content policies that apply to everyone, not just Marketing. |
| Creative autonomy vs. standardization | As more people – also outside of the Marketing Team – can generate content, maintaining tone, voice, and brand coherence becomes harder. | Forces marketers to provide toolkits, brand playbooks, and approval paths that empower non-marketers while protecting brand integrity. |
External Challenges (Market, Discovery & Demand)
These challenges emerge from how AI is reshaping the external environment in which marketers and brands operate. As AI-powered agents rewrite how audiences discover, interpret, and engage with content, marketers face reduced visibility, blurred attribution, and diminishing control over narrative.
| Challenge | Description | Impact |
|---|---|---|
| Discovery disruption | AI agents (e.g., Gemini, ChatGPT, Perplexity) are increasingly answering questions directly in search results or their own interface, removing the need for users to click through to brand websites. | Forces marketers to rethink how they influence customer understanding when they no longer control the full narrative—or even the platform where it’s told. |
| Brand invisibility | Even if your content informs AI outputs, your brand may not be mentioned or credited. | Forces content creators to design assets and messaging that can survive summarization, remixing, and third-party mediation while still signaling your brand DNA. Forces organizations to consider their brand as a flag around which a community rallies, to build these communities, brands need to have a fine understanding of what medias they consume. |
| Lead generation uncertainty | Traditional funnels (form fills, landing pages, gated content) may no longer apply when customers don’t engage on your owned platforms. | Forces a shift toward outcome-based measurement, deeper CRM integration, and new ways to capture intent signals beyond click-based CTAs. |
| Search behavior shifts | SEO strategies built around traditional keyword optimization may become less effective as users rely more on conversational queries to get instant answers. | Forces teams to focus on structured data, semantic relevance, and being the “source of truth” AI models rely on; not just ranking high on SERPs. |
| Signal dilution (in relation to USPs) | With AI summarizing and remixing content, your differentiated messaging can be lost or homogenized. | Forces stronger, more distinct brand voice and positioning so that your point of view remains recognizable, even when filtered through AI. |
| Mistrust of AI-generated content | Some audiences may be skeptical of content not clearly authored or curated by a human—especially in high-trust categories. | Forces marketers to disclose, humanize, and contextualize AI-assisted content—and to know when human-authored storytelling is non-negotiable. |
AI in Marketing: Use Cases Across the Value Chain
From understanding the impact of AI to applying it in daily work: this section offers offers a landscape of practical, real-world use cases, grouped by functional area. While non-exhaustive, it is designed to inspire teams with what’s possible—and to highlight where human judgment, brand integrity, and ethical standards remain critical.
Keep in mind: different models have different strengths. Success depends not just on applying AI, but on choosing the right model or tool for each type of task—whether it’s insight generation, content creation, or optimization.
💡 Strategy & Insights
- Persona Research Summaries
- Competitive Landscape Analysis
- Audience Behavior Prediction
- A/B Test Recommendations
- Trend Identification (e.g., through social listening)
- Market Segmentation Suggestions
✅ AI works well for Identifying early trends and summarizing vast research (e.g., social listening or persona inputs)
⚠️ Use with caution because AI can reinforce existing biases or oversimplify nuanced segments; especially when based on incomplete, outdated, or skewed datasets. Remember: AI is only as good as the data it has access to, and without human oversight, it may draw confident conclusions from flawed foundations.
🎯 Campaign Planning & Management
- Journey Mapping Suggestions
- Channel Mix Optimization
- Campaign Timeline Generation
- Asset Checklists & Workback Plans
- Performance Forecasting
✅ AI works well for Optimizing channel mix and suggesting campaign schedules based on historical patterns.
⚠️ Use with caution because AI suggestions may ignore brand timing, internal dependencies, or key market moments.
🤝 Sales & Enablement
- Sales Battlecard Drafts
- Deck Co-Creation (with placeholders or GenAI slides)
- Objection Handling Scripts
- Training Scenario Generation
- Internal Enablement Content
✅ AI works well for Drafting sales battlecards or objection handlers using previous call transcripts or product FAQs.
⚠️ Use with caution because Tone and context can get lost, especially in high-stakes sales conversations requiring nuance.
📈 Analytics & Optimization
- Performance Report Summaries
- Insights Narratives (turning charts into plain language)
- Ad Spend Optimizations
- Anomaly Detection in Web Traffic
✅ AI works well for Summarizing performance data and creating plain-language insights from dashboards.
⚠️ Use with caution because Anomalies may be flagged too late or misinterpreted without human validation.
🛠 Content & Creative
- Copy Drafting & Ideation (emails, ads, social posts, scripts)
- Visual Generation (thumbnails, social graphics, illustration prototypes)
- Video Creation & Editing (promo reels, AI avatars, subtitles)
- Content Repurposing (longform to shortform, blog to social, written to audio)
- SEO Optimization (metadata, keywords, semantic structuring)
- Tone & Voice Adaptation (translating or adapting for different audiences)
✅ AI works well for Speeding up copy ideation and generating visual prototypes for social and digital channels.
⚠️ Use with caution because AI may produce off-brand or generic creative output without proper curation.
📬 CRM & Personalization
- Email Subject Line Testing
- Personalized Email/Message Suggestions
- Lead Scoring with AI Signals
- Customer Journey Tailoring Suggestions
✅ AI works well for Testing email subject lines and auto-generating personalized message variants.
⚠️ Use with caution because Over-personalization can feel invasive or uncanny, hurting trust if not carefully balanced.
🧘 Personal Productivity
- Meeting Summaries
- To-Do List Generation
- Smart Brief Writers
- Prompt Libraries for Repeat Tasks
- Time Management Assistants (e.g. via calendar AI)
✅ AI works well for Summarizing long meetings and turning action points into structured to-dos.
⚠️ Use with caution because Summaries can omit emotional cues or strategic subtext—leading to misalignment or rework.
Maturity Models for AI-Driven Marketing Teams
Goal: Move from “AI-curious” to “AI-fluent” while maintaining ethics, quality, and creativity.
👥 People
AI requires people—not just platforms. Marketers need to develop new skills, rethink creativity, and align ethically. The People pillar ensures the team has the confidence, literacy, and ethical compass to work effectively with AI.
| Subdomain | Activity | Maturity Indicators | Metrics to Consider |
|---|---|---|---|
| Skills Mapping & Training | Inventory current AI skill levels and plan upskilling paths. | Clear skill taxonomy (e.g., prompt design, tool fluency). | % of team assessed, % trained to target level, AI fluency benchmarks. |
| Hiring Standards | Define AI expectations in job descriptions (like languages or software). | JD templates include AI proficiency levels per role. | % of new hires with target AI level. |
| Ethical Awareness / Ethical Use | Build cultural literacy around AI & generational/creative sensitivities. Ensure alignment with ethical standards, respect of intellectual property, promote inclusivity, fairness, and brand integrity. | Team-wide alignment on ethical content use. | % of team completing AI ethics module. |
| Creative Judgment | Build literacy in when to value human creation, curation, or augmentation. | Case-based training on quality thresholds and use context. | Internal audit: % content hitting quality standards. |
| Employee Governance | Clear do’s/don’ts for using GenAI in and outside Marketing. | Internal policy and training for all employees on creative responsibility. | # of reported violations, engagement in guidelines training. |
| Stage | Characteristics | Where we are today |
|---|---|---|
| 1 – Aware | Teams hear about AI tools but don’t engage. No skills mapping or training. | |
| 2 – Experimenting | A few individuals use tools ad hoc, with mixed outcomes. Skepticism persists. | |
| 3 – Equipped | Skills baseline established. Training and policies introduced. Roles updated. | |
| 4 – Operational | Team-wide fluency. AI responsibilities part of onboarding and performance goals. | |
| 5 – Strategic | AI expertise is a competitive advantage. Clear mastery levels per role. AI skills integrated into recruitment, training paths, and succession planning. |
⚙️ Processes
The way content is planned, created, reviewed, and governed must evolve alongside AI. The Process pillar ensures that AI is embedded intentionally—not chaotically—into workflows, policies, and quality controls.
| Subdomain | Activity | Maturity Indicators | Metrics to Consider |
|---|---|---|---|
| Content Lifecycle | Define when GenAI is helpful (ideation, drafting, polishing). | AI decision tree integrated in briefing or workflow process. | % content using GenAI appropriately, feedback scores. |
| Quality Control | Align on internal vs external quality standards. | Quality review stage defined based on content tier. | Rework ratio; external error rate. |
| Review & Curation | Embed checkpoints to ensure AI outputs meet brand, tone, facts and are legally appropriate. | Content “human checkpoint” for curation/approval. | % of content human-reviewed; average approval cycle time. |
| AI Use Governance | Documented policies for AI usage, disclaimers, citations, reuse. | AI Policy Handbook rolled out. | Employee understanding score in regular pulse survey. |
| Feedback Loops | Learn from wins/mistakes, refine playbooks. | Monthly AI retro reviews or creative post-mortems. | # of insights actioned per quarter. |
| Applied Learning & Experimentation | Create recurring forums (e.g. “The Test Bench” in All-hands team meeting) to share AI use cases, demos, and lessons (good or bad). | Experimentation is normalized. Teams contribute learnings and failures openly. | # of contributions per quarter, % team participation, # of pilots transitioned into workflows. |
| Stage | Characteristics | Where we are today |
|---|---|---|
| 1 – Aware | Teams are aware that AI could affect processes but haven’t made any changes. | |
| 2 – Experimenting | Small-scale, isolated tests of AI in specific workflows. No documentation. | |
| 3 – Equipped | AI points of use are defined in workflows. Quality checks and review steps added. | |
| 4 – Operational | AI is embedded into key content, review, and governance workflows. Feedback loops active. | |
| 5 – Strategic | Workflows are continuously refined based on AI learnings. Creative and ethical standards are enforced and optimized. |
🛠 Technology
Tools should accelerate—not complicate—work. The Technology pillar ensures the right AI tools are in place, securely integrated, and delivering measurable impact across the marketing stack.
| Subdomain | Activity | Maturity Indicators | Metrics to Consider |
|---|---|---|---|
| Tool Stack | Choose the right AI tools for the job (text, image, video, etc.). | Teams have documented a tool-to-task guide, mapping primary AI tools to their best-fit use cases; regular reviews. | Tool adoption rate; tool-specific usage stats. |
| Integration | Ensure tools are embedded in core marketing workflows. | Templates, briefs, CMS, or DAM systems integrate AI. | % of briefs using AI templates. |
| Access Control | Right access to the right people at the right time. | Admin roles and usage logs. | # of access misuses or unauthorized content uploads. |
| Security & IP | Understand what goes into models and protect brand IP. | Vendor audits, legal review, NDA workflows. | % tools reviewed & approved by legal/security. |
| Performance Tracking | Measure output gains from AI tools (speed, quality, engagement). | Side-by-side tests: with AI vs. without AI. | Time-to-publish, CTR uplift, engagement delta. |
| Stage | Characteristics | Where we are today |
|---|---|---|
| 1 – Aware | Teams are aware of GenAI tools but don’t use them meaningfully. No official stack. | |
| 2 – Experimenting | Individuals bring in tools without oversight. Security risks emerge. | |
| 3 – Equipped | Tool selection begins. Approved vendors. Access managed. First use guidelines. | |
| 4 – Operational | Tools embedded into core systems (CMS, DAM, CRM). Usage monitored. | |
| 5 – Strategic | Tool stack is optimized for ROI and adoption. Integrated across ecosystem. Performance tracking informs usage. Legal, security, and branding are safeguarded by design. |
Cross-cutting Components
Beyond pillars and playbooks, these components help teams embed responsibility, quality, and clarity across everything they do with AI.
- Ethics & Sensitivity: Integrated into training, tools, and workflows (e.g., flagging AI-generated images mimicking artists without consent).
- Content Quality Matrix: Internal framework that defines what’s OK at each stage (e.g. rough GenAI sketch for internal alignment = ✅; public post = ❌ unless curated).
- Creative Role Taxonomy: Guidelines for when to use human-only, AI-assisted, or AI-only content creation based on purpose and audience.
- Governance: Clear policies for internal and external content use, accountability models, and documentation needs.
Scaling AI Confidence: From Team to Individual
This individual-level Marketer Growth Framework builds on the “People” pillar by mapping how AI expectations grow across different modern marketing roles.
Originally adapted to support the growth and development of a Marketing team I led in the past, this framework was inspired by the Developer Growth Framework by Tamara Buckland (@LadyGalaxyNZ). It has been updated to integrate AI-related skills—highlighted in light green.
| #build | #deliver | #connect | #lead | |
|---|---|---|---|---|
| Development of high quality marketing activities. Leveraging empathy for clients/customers/community to understand their problem or opportunity, and using that knowledge to generate awareness and leads. | Delivering quality projects on time and demonstrating best practice for managing their work. Communicating effectively about project work with people at all levels. | Building and promoting the culture of the company. Representing the company externally and building the wider community. Developing the team by sharing knowledge and skills. | Developing leadership skills to help others succeed, advocating for team members, supporting well-being, and actively contributing to a safe and effective work environment. Proactively contributing to the growth of the organisation. | |
| Junior Marketer | You have a solid grasp of foundational marketing concepts and are actively expanding your knowledge and skills. You’re familiar with your team’s tools and workflows, and beginning to understand marketing best practices and productivity techniques. You’re curious about topics such as automation, analytics, lead generation, event planning, content and thought leadership, ABM, advertising, PR, and CRM. You are starting to explore generative AI tools (e.g., ChatGPT, Canva AI) to support content ideation, research, or drafting, and have a basic understanding of prompt formulation. | You are capable of taking on small, well-scoped components of larger projects. With guidance from more senior team members, you complete these tasks within reasonable timeframes while maintaining a sustainable pace. You’re comfortable asking for support when needed and do so regularly. When facing obstacles, you work alongside teammates to approach them with persistence and a positive mindset. You begin to use AI tools to structure or draft simple campaign elements, developing confidence in applying them to basic marketing tasks. | You are developing your communication skills across a variety of settings, such as team stand-ups, client meetings, retrospectives, and planning sessions. You’re learning to give constructive feedback to peers and managers, and you contribute to a collaborative environment by supporting new team members and sharing knowledge openly. You reflect on company values and culture and look for ways to positively contribute. You are beginning to explore how AI can support collaboration—for example, by generating meeting notes, drafting internal updates, or organizing shared information. | You respect and actively participate in team processes, offering constructive feedback to help improve how the company operates. You begin to recognize the strengths and development areas of your teammates and use available tools and rituals to support a healthy, inclusive, and collaborative work environment. You help identify blockers and support your team in addressing them. You’re developing emotional intelligence and learning to navigate team dynamics with empathy and kindness. You follow team guidance on ethical AI use and ensure your work aligns with brand standards and content quality expectations. |
| Intermediate Marketer | You have a solid understanding of core marketing concepts and are focused on deepening your expertise. You actively contribute to improving team tools, processes, and productivity. You bring hands-on experience across various marketing disciplines such as automation, analytics, lead generation, SEO, product marketing, social media, events, content and thought leadership, ABM, advertising, PR, and CRM. You confidently use generative AI tools to enhance your efficiency—whether for copywriting, image generation, or content summarization—and apply prompt best practices to ensure relevance and quality. | You independently deliver high-quality marketing activities and know when to seek support to stay efficient and effective. You communicate clearly across the team, focusing on productive collaboration and clarity. You take initiative to improve workflows and processes, contributing to greater team efficiency. You approach challenges with resilience and view obstacles as learning opportunities. You integrate AI into campaign planning and execution—using it to streamline asset creation timelines, increase speed, and support iteration without compromising quality. | You mentor junior team members by guiding them toward insights rather than offering ready-made answers. You actively participate in the hiring process, helping the team make thoughtful, inclusive, and impactful recruitment decisions. You foster a sense of belonging by stepping up to build connectedness and taking tangible actions that contribute to an inclusive team culture. You share effective AI prompts, tools, and workflows with peers, encouraging experimentation and knowledge exchange across the team. | You actively support and advocate for junior team members, helping them navigate project challenges and build confidence. You identify opportunities to improve team processes and suggest thoughtful changes that enhance collaboration and efficiency. You contribute to a positive and inclusive team culture, and you support others with empathy, kindness, and professionalism—especially during moments of stress or challenge. You advocate for responsible AI use in team discussions, promoting awareness of ethical considerations and reinforcing brand standards in how AI is applied. |
| Senior Marketer | You confidently manage large-scale campaigns and budgets, demonstrating a strong grasp of KPIs and performance targets. You understand your audience’s pain points and craft messaging that resonates. You can define multi-tactic marketing strategies, allocate budget effectively, and incorporate best practices and emerging trends into your work. You proactively form your own point of view and make well-informed recommendations to guide decision-making. You select the most appropriate AI tools based on the task at hand, and tailor AI-generated outputs to align with brand tone, campaign objectives, and audience expectations. | You lead and contribute to the successful delivery of complex projects alongside your team. You proactively share information, seek and give feedback, and ensure clear communication across multiple stakeholders. You help others improve their ability to deliver high-quality work and take initiative in setting the tone, pace, and structure for effective project execution. You model resilience and a positive, solution-oriented mindset—supporting junior team members in developing the same approach. You lead projects that strategically apply AI to accelerate execution, enhance personalization, or enable faster iteration—ensuring outcomes remain aligned with brand and business goals. | You actively share your expertise with other marketers and contribute to the company’s internal knowledge base. You work to enhance the organization’s reputation externally—helping attract top talent and positioning the company as a thought leader. You foster team collaboration and a culture of openness, curiosity, and continuous learning by encouraging knowledge exchange and supporting a growth mindset. You help integrate AI tools into cross-functional workflows and act as a bridge—demystifying AI for non-experts and enabling more confident, effective adoption across teams. | You inspire and support a small group of teammates, encouraging them to grow beyond their comfort zones. You create repeatable processes and tools that address ongoing organizational challenges. You actively promote psychological safety and open conversations about mental health, and you support the overall well-being of your team. You assist managers in navigating performance challenges and are able to hold courageous, constructive conversations. You consistently role model empathy, compassion, and emotional intelligence in a variety of settings. You coach others on how to use AI responsibly, including prompt design, ethical boundaries, and real-world use cases. You help shape team norms around AI adoption and raise awareness of where human judgment and creative oversight are essential. |
| Lead Marketer | You bring deep marketing expertise and stay ahead of evolving trends and strategies. You proactively research new approaches, propose innovative ideas to leadership, and help shape strategic decisions. You serve as a marketing-savvy partner within cross-functional teams—asking the right questions, challenging assumptions, and ensuring campaign designs are aligned with business objectives. You play a key role in building and scaling a marketing team that meets the company’s growing needs. You guide others in the responsible use of AI and lead the development of AI-integrated workflows across the marketing stack. You ensure ethical standards are upheld, efficiency is enhanced, and team adoption is well-supported. | You effectively lead and deliver complex projects that involve multiple stakeholders and high levels of organizational impact. You communicate complex ideas with clarity, align diverse teams, and champion high-quality outcomes. You identify and address systemic challenges, taking proactive steps to elevate delivery standards. You drive change with confidence, modeling a solution-oriented mindset and helping others see obstacles as opportunities. You define clear success metrics for AI-assisted marketing execution and mentor teams on when and how to apply AI responsibly. You promote thoughtful adoption by balancing speed and scale with creative and strategic integrity. | You foster a culture of mentorship by encouraging and enabling knowledge-sharing across the team. You actively contribute to positioning the company as an innovative, values-driven workplace—both internally and externally. You play a leading role in hiring, from sourcing and interviewing to making inclusive, strategic talent decisions. You recognize strengths in others and help them share their expertise—whether within the company or on a larger stage. You champion AI literacy across the organization, helping set cultural norms around transparency, ethics, and confident experimentation. You ensure that AI is understood not just as a tool, but as a mindset shift that requires openness, shared learning, and thoughtful integration. | You manage complex interactions across teams and functions, promoting best practices and modeling a high standard of leadership. You identify systemic issues and underlying dynamics that impact organizational health, and you take proactive steps to address them. You advocate for team and individual needs, mediate escalated situations with care, and help empower underperforming teams. You also support others in navigating emotional dynamics with empathy and compassion. You shape policy and norms for AI use across the marketing organization. This includes defining maturity expectations by role, mentoring others in prompt design and ethical boundaries, and representing Marketing’s perspective in broader AI strategy discussions. You champion AI literacy, promote transparency, and elevate the responsible adoption of AI across the company. |
Ideas / Additions Under Consideration 🙂
Tool-to-Task Reference Table
A practical map linking common marketing tasks to the types of AI tools best suited for each (e.g., LLMs for writing, generative models for visual creation, predictive models for performance forecasting).
Types of AI Models in Marketing
A marketer-friendly primer explaining foundational model types—LLMs, generative media, retrieval-augmented generation, etc.—for better tool selection and understanding.
What Did We Learn from Past Fundamental Shifts
“Under mounting pressure to deliver more, faster, and with sharper personalization, marketers must now navigate a world where content is abundant, attention is scarce, and differentiation is harder than ever.”
These words have been said before, about the internet, about social media, etc. How is this different or what can we learn from these.
Common Pitfalls & Classic Mistakes
A new section that captures frequent missteps (e.g., over-automation, prompt misuse, brand dilution) and how to avoid them.
Prompt Design Principles
A lightweight guide with examples of effective prompt formats tailored to marketing use cases (ideation, outlining, summarization, etc.).
Ethics & Responsibility Checklist
A simple checklist to evaluate whether an AI-generated output meets ethical, legal, and brand standards before publishing.
AI ROI & Efficiency Measurement
A framework or template for measuring the time saved, quality improvements, and performance impact of AI in specific workflows.
AI Use Policy Template
A customizable one-pager covering internal usage rules, attribution, disclaimers, and responsibilities for AI-assisted marketing.
