by Lori Berson | Sep 17, 2026 | Creative Services, Digital marketing, Marketing, Marketing Strategy
- Activity doesn’t equal impact: 95% of B2B leaders admit their execution needs work; the core issue is a lack of integration across channels, not a lack of output.
- Strategy must precede tactics: Define the core business problem, primary target audience, and success metrics before launching campaigns, creating content, or buying new tools.
- Creative work drives true differentiation: Modern AI makes asset production fast, but strategic creative execution is what turns abstract business goals into clear, memorable value propositions.
- Brand and demand are interdependent: Generating short-term leads is significantly harder without long-term brand equity; every touchpoint must reinforce the same core value.
- AI scales your current baseline: Technology accelerates whatever strategy you give it; automating unclear positioning or generic messaging only produces mass confusion faster.
- Marketing belongs in core growth planning: Expecting revenue results requires involving marketing early across positioning, buyer needs, and sales alignment, rather than treating it as a downstream production vendor.
Most B2B companies already invest heavily in marketing. They maintain websites, run email programs, create social content, use automation tools, analyze data, and test AI. But more marketing does not always produce better business results.
New research from Walker Sands shows a clear gap. Almost every B2B leader surveyed said they understand what modern marketing should look like. But 95% also said their marketing must improve to compete with leading brands. The fundamental issue isn’t a lack of activity; it’s a lack of integration.
Strategy must guide the work. Creative must make the strategy clear and useful. Execution must stay consistent. Measurement must show whether the work supports the business goal.
When every element of your marketing engine works in unison, it stops being a cost center and starts driving measurable financial outcomes:
- Lower Customer Acquisition Cost (CAC): Strategic alignment eliminates wasted spend on non-performing tactics and disconnected tools.
- Faster Pipeline Velocity: Consistent, compelling messaging across sales and marketing shortens complex B2B buying cycles.
- Higher Deal Win Rates: Clear, differentiated creative positioning protects margins against lower-cost competitors.
Disconnected Marketing vs. Connected Marketing
| Marketing Area |
Disconnected Approach |
Connected Approach |
| Content Strategy |
Produced for volume based on team assumptions. |
Built to solve specific buyer questions and needs identified by sales. |
| Technology & AI |
Mass produces generic assets across isolated tools. |
Scales approved positioning and accelerates personalized buyer journeys. |
| Measurement |
Focuses on clicks, opens, impressions. |
Focuses on marketing activity to business outcomes. |
| Sales Alignment |
Sales creates its own materials because existing content isn’t useful. |
Sales uses marketing materials to close deal conversations. |
Start with Strategy, Not Tactics
The Study reveals 67% of marketing leaders struggle to identify which business results executives expect them to impact, while 79% find it difficult to demonstrate marketing ROI altogether.
This gap creates a basic problem: you cannot measure marketing performance effectively if leadership hasn’t agreed on what marketing must achieve. This is why strategy must come before tactics. Before your launch another campaign, produce more content, redesign a website, or add a new tool, ask your team:
- What specific business problem must we solve?
- Which audience matters most right now?
- What must the audience understand and act on?
- Why should buyers choose us over the competition?
- Which marketing activities can produce the desired outcome?
- How will we measure success?
These questions help turn marketing from a list of tasks into a coordinated business function.
Many Problems Start Before Execution
B2B leaders identified five areas where their marketing needs to improve:
- Measurement and performance insights.
- Consistent marketing operations.
- Cross-channel coordination.
- Testing and validating new channels.
- Long-term brand building and awareness.
Notice what is not on this list. Leaders aren’t asking for more emails, higher content volume, or more social posts. Their challenges start much earlier. Companies need clear priorities, channels to support each other, distinct brand positioning, useful performance data, and operational systems that keep teams aligned.
These are strategy problems before they become production problems.
Strategy Is Not Enough
A good strategy can still fail if the execution gets ignored. In many B2B organizations, creative work is treated as a final design step. That narrow view misses its true value: creative strategy helps turn business goals into messages that people can understand, remember, and act on.
While strategy defines the target audience and value proposition, creative work communicates that value. For a B2B organization, strategic creative work can:
- Explain complex services in simple terms.
- Build a clear and consistent visual identity that builds immediate recognition.
- Turn product features into meaningful customer outcomes.
- Create campaigns that help sales teams start better conversations.
- Make complex information easier to compare.
- Show buyers why the company is different.
This work matters even more because AI can create functional content in seconds. While modern AI drastically speeds up asset production, it does not guarantee differentiation. True value comes from knowing what to say, why it matters, and how to communicate it clearly.
Brand and Demand Must Work Together
Companies often treat long-term brand building and short-term demand generation as competing priorities, when they should support each other. The data shows that B2B leaders recognize long-term brand building as an area that needs improvement. That matters because demand generation becomes harder when buyers do not know your company, understand your value, or see a clear difference between you and your competitors.
A connected strategy harmonizes brand and demand across every touchpoint. For example:
- Your website supports the same value proposition used by sales.
- Your thought leadership validates your expertise.
- Your email marketing matches the tone and authority of your social channels.
- Your sales materials continue the same message used in campaigns.
Connected marketing also requires feedback from sales. Sales teams hear buyer questions and objections directly. Marketing can use that information to improve strategy, content, and messaging.
AI Scales Good Marketing and Bad Marketing
B2B leaders also show strong interest in AI and marketing automation. AI can help with research, content drafting, data analysis, and repetitive tasks. But technology cannot fix a weak strategy.
- If your positioning is unclear, AI can create more unclear content.
- If your messaging is generic, AI can create more generic content.
- If teams do not agree on priorities, automation can help them move in different directions faster.
Before asking “What can we automate?” ask “What must we improve, and where can technology help?” First, get the direction, then use technology to scale the work.
Marketing Must Be Part of Growth Strategy
The research also shows a gap between expectations and involvement. 89% of B2B leaders expect marketing to help drive revenue. But only 45% said executive leaders view marketing as a core part of growth strategy. That creates a problem.
Companies expect marketing to support growth, but some still treat it mainly as a production function. Marketing should be involved earlier. It should help connect:
- Business goals and revenue targets.
- Buyer needs and pain points.
- Competitive positioning and messaging.
- Creative direction and sales enablement.
- Marketing channels and technology.
- Measurement frameworks and analytics.
When strategy and creative work together, business goals become easier to communicate and support through marketing. Strategy without strong creative can be difficult to see. Creative without strategy can attract attention without supporting the business goal. The strongest marketing connects both.
Quick Audit: Is Your Marketing Connected?
Ask your leadership team these three questions:
- Can everyone identify your top 3 marketing priorities?
- Does your primary sales presentation use the same core positioning as your website?
- Can your marketing reports connect key campaigns to qualified pipeline or revenue?
If the answers are not consistent, your marketing may have an alignment problem. That does not mean you need more tactics. It may mean the existing work needs to connect more clearly.
Your 30-Day Starting Point
Start with a simple review. Gather your:
- Website homepage.
- Main sales presentation.
- Latest email campaign.
Compare them side-by-side. If the positioning, tone, and value proposition don’t match, you have found your primary growth bottleneck.
Turn Disconnected Marketing Into Connected Marketing
Adding more tactics will not fix unclear priorities, inconsistent messaging, or disconnected channels.
BersonDeanStevens helps B2B companies connect strategy and creative execution so their marketing supports clear business goals. We help companies improve positioning, messaging, creative direction, content, campaigns, and marketing systems so the parts work together.
Is Your Marketing Working Together?
Schedule a complimentary call with Lori at lberson@bersondeanstevens.com or use her calendar to identify where your strategy, creative, or execution may need better alignment.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
by Lori Berson | Sep 15, 2026 | AI, Content Marketing, Creative Services, Design, Digital marketing, Marketing, Marketing Strategy
- Speed Is No Longer a Differentiating Advantage: As AI makes competent marketing instantaneous for everyone, output volume and speed lose their competitive edge. Value shifts from how fast you produce to how distinctly you position your message.
- AI Excels at Patterns; Human Strategy Requires Originality: AI generates content based on existing data, which leads competing brands into a generic “sea of sameness.” Creative strategy uncovers unique insights and distinct positions that competitors cannot easily replicate with the same prompts.
- Creativity Is a Strategic Asset, Not Aesthetic Polish: In complex industries like financial services and health insurance, strong creative strategy isn’t just visual design. Its primary job is to simplify intricate rules, clarify dense value propositions, and turn complex ideas into memorable messaging that drives sales.
- Constructive Pushback Protects Your Investment: AI blindly executes instructions regardless of their strategic value. Experienced creative partners interrogate the brief, eliminate clutter, and prevent brands from spending resources on polished work that fails to address the root business problem.
- The Winning Formula Balances AI Efficiency with Human Judgment: High-performing marketing teams use AI to accelerate research, organize data, and streamline execution—while reserving strategy, brand voice, empathy, and creative direction for human talent.
AI has made marketing faster and easier to produce. Almost any business can now generate headlines, images, emails, presentations, videos, and campaign ideas in minutes. While AI shifts output into overdrive, it presents a double-edged sword: when every brand uses the same toolset, speed alone ceases to be a competitive advantage. In fact, the opposite is true. As AI makes it easier to produce competent marketing, distinctive creative thinking becomes exponentially more valuable.
We are already surrounded by copycat collateral like identical headlines, mirrored site layouts, generic illustrations, and recycled buzzwords like “transformation,” “growth,” and “customer experience.” The work may look polished, but much of it is easy to forget. Creativity is not a decorative layer applied after the strategy is complete; it is a strategic business asset.
AI Can Create More. It Does Not Guarantee Differentiation.
While I actively use and advocate for AI tools to accelerate research, organize information, analyze data, and streamline production, output is not strategy. As analyst Brian Solis highlights, AI extends human capability, but human creativity remains the sole engine for creating memorable, meaningful brand experiences.
That distinction matters. AI excels at identifying and repeating patterns based on existing data. Creative strategy asks a fundamentally different question: What should we create that is different, useful, and right for this specific audience? That might mean finding a simpler way to explain a complicated financial product, crafting a campaign competitors haven’t considered, or turning a dense carrier announcement into something brokers can quickly digest and act on. AI can support that work, but the strategic thinking behind it cannot be outsourced.
The Bigger Risk Is Forgettable Marketing
AI-generated marketing is rarely bad; in fact, it’s often perfectly adequate. That adequacy is precisely the risk. If competing companies use AI to research the same audiences, analyze the same competitors, and follow the same content structures, their brand messaging inevitably gravitates toward the middle.
Professional creative work must move in the opposite direction, carving out a distinct message, visual style, and point of view that a company can truly own. As Marketing-Interactive recently noted, there is a growing demand for creative leaders who can help brands stand out in a growing “sea of sameness.” AI provides speed and scale, but people supply the judgment, empathy, insight, and original thinking required to make an impact. The question is no longer just, “Can AI create this?” A far better question is: What can our brand create that a competitor cannot easily reproduce with the same tools?
Creativity Has a Business Job
Creative services are too often mischaracterized as an aesthetic expense, a tool to make a brochure look nicer, a presentation cleaner, or a campaign more attractive. Those are mere outputs. The real job of creative work is to help a business communicate clearly and compete aggressively.
Strong creative strategy transforms complex ideas into intuitive messaging that earns attention, builds credibility, supports sales, and reinforces brand value. It makes similar products feel meaningfully different, an essential capability in heavily regulated industries like health insurance and financial services. These sectors contend with technical products, intricate compliance rules, homogeneous competitors, long sales cycles, and high trust barriers. When faced with these challenges, more information is rarely the answer; better, clearer communication is.
Creative Strategy Makes Complex Information Useful
Consider a General Agency communicating a major carrier change. The source documentation often spans network updates, benefits, eligibility requirements, and broker deadlines. The creative challenge isn’t just making those documents visually appealing; it’s deciding what the broker needs to know first, what changed, who is affected, and what to do next. That is strategy expressed through design and content.
Financial services face the same obstacle. An asset-based lender, wealth management firm, or RIA may possess deep expertise yet sound indistinguishable from competitors by relying on tired phrases like “customized solutions,” “trusted partner,” or “decades of experience.” While true, these claims are easy for anyone to make. Creative strategy digs deeper to uncover why clients truly choose your firm, what unique market friction you solve, and how to translate those answers into memorable marketing that drives decision-making.
Good Creative Partners Do More Than Execute
Experienced creative partners deliver an indispensable asset that AI cannot replicate: constructive pushback. Strategic creators do not simply execute requests blindly; they interrogate the work to protect your investment.
They ask the hard questions: Does this headline actually say anything? Does the site focus on the customer or the company? Are we cramming six messages into a campaign when the audience will only remember one? Sometimes the most valuable creative contribution is recognizing that the initial request won’t solve the underlying problem, saving businesses from spending money on polished work that fails to move the needle.
How I Approach Creative Work at BersonDeanStevens
At BersonDeanStevens, I unite strategy, creativity, and technology into a cohesive workflow. Every project begins with the core business problem: understanding who we are targeting, what drives their decisions, what prevents them from acting, and what distinct positioning your company can credibly own.
Only after defining the strategy do we craft the execution, whether through brand positioning, integrated campaigns, interactive tools, web design, thought leadership, or AI-assisted marketing workflows. AI speeds up execution, but speed only helps when moving in the right direction. The underlying strategy and brand voice must remain solid.
Test Your Marketing for Sameness
Before publishing your next AI-supported campaign, evaluate your content against these quick criteria:
- The Logo Swap: Could a direct competitor put their logo on this piece and publish it without changing a word?
- Specific Value: Are you delivering a specific, actionable insight or repeating standard industry jargon?
- Brand Voice: Does the tone, style, and visuals uniquely reflect your company’s identity?
- Clarity & Memory: Does the execution clarify a complex idea and give the audience a compelling reason to remember it?
If these questions highlight a gap, generating more content will only amplify the issue. Fix the underlying strategy first.
Grab the AI-Era Creative Partner Checklist to evaluate your current agency or internal workflow against 8 critical differentiation standards.
Efficiency Is Easier to Buy. Originality Is Not.
As AI tools mature, production costs will drop, output speeds will rise, and smaller teams will produce larger volumes of content. However, when everyone can produce polished work instantaneously, volume and polish lose their premium value. Competitive advantage shifts from who can create more to who can determine which ideas are worth pursuing.
Businesses do not need to choose between AI efficiency and human creativity. The most successful organizations leverage AI to automate research, analyze data, and streamline production, while relying on experienced human talent for strategy, judgment, and original direction.
If your marketing is starting to blend in, contact BersonDeanStevens to discuss how strategic positioning and distinct creative execution can give your brand an unmistakable edge.
To get started, contact Lori at lberson@bersondeanstevens.com or schedule a complimentary call.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
by Lori Berson | Sep 5, 2026 | AI, Digital marketing, Marketing, Marketing Strategy
Key Takeaways
- Most competitive research tells you what already happened. The real value comes from understanding what those changes mean for your business.
- Focus on three questions: What does this mean for us? Where are we exposed? Where is the opening?
- Use AI for repetitive monitoring, such as tracking messaging, pricing, sentiment, content, and positioning changes.
- Use people for interpretation, strategy, judgment, and deciding what to do next.
- You do not need a large technology stack. Start with simple monitoring tools and use AI to help analyze what you find.
- Do not ask AI only for summaries. Ask specific questions that lead to decisions and actions.
- The advantage is not simply faster competitive reports. It is turning competitor data into better recommendations and better decisions.
- Access to AI is no longer the differentiator. Knowing what to ask and how to act on the answers is.
Somewhere in your marketing files, you probably have a competitor tracking document. Maybe it is a dashboard. Maybe it is a weekly report that someone updates every Friday.
It feels organized. It feels like you are staying on top of things. But much of that information tells you what already happened.
That is the problem I see with most competitive research.
Watching a competitor and understanding what their actions mean are two different jobs. Most teams focus on the first one.
Social listening tools count mentions and measure sentiment. Weekly reports summarize recent activity. Those tools can be useful, but they usually look backward. They tell you what changed. They do not always tell you what is shifting, what might happen next, or what any of it means for your business.
AI is starting to change that.
The Three Questions That Actually Matter
I have watched companies treat competitive research like a homework assignment for years. They collect the data. They organize it into a presentation. They discuss it in a meeting. Then the report gets filed, and very little changes.
Tracking competitors is the easy part.
The work that can actually move a business happens when I ask three questions:
- What does this mean for us?
- Where are we exposed?
- Where is the opening?
Everything else is data collection.
If a competitive report does not help answer those questions, I do not think it is doing enough. You have information, but you do not yet have strategy.
This is where I think AI genuinely earns its place in the process.
AI is good at the repetitive monitoring. It can watch for changes in messaging. It can track sentiment across reviews and online discussions. It can identify when a competitor changes its content, pricing, positioning, offers, or priorities.
An experienced analyst can closely track one or two competitors. AI can help monitor many more sources, every day, without the same limits on time and attention. That matters because it gives people more time to focus on the work that requires judgment.
I can spend less time gathering information and more time asking:
- What does this mean?
- Where are we vulnerable?
- What should we do next?
Two Tools, Not Twenty
I don’t think you need a stack of twelve platforms to do this well. You only need two things: a way to watch and a way to think.
Watching means monitoring.
There are dedicated competitive intelligence tools for this. Some enterprise platforms can cost tens of thousands of dollars a year. Most companies do not need to start there.
You can build a lean version yourself.
Set Google Alerts for competitors and their leadership teams. Use a traffic analysis tool to monitor their websites. Review customer comments and reviews. Collect important observations in one shared document each week. It is partly manual, but it works.
Thinking means synthesis.
This is where I use an AI model such as Claude. I can give it a week of observations and ask the three questions, one at a time.
I do not ask: “Tell me about this competitor.”
That usually gives me a summary.
Instead, I ask: “What does this mean for us?”
Then I push further.
If the answer is too general, I ask for the evidence behind it. I ask what action the company should take. I ask what I would actually do differently on Monday because of what the model found.
That is when the analysis gets more useful.
AI Raises the Baseline. It Does Not Do the Thinking for You.
This is the part I think gets lost in much of the AI discussion.
The value is not simply faster reports. The real value is better thinking.
Teams can spend less time collecting and organizing information and more time walking into leadership meetings with recommendations instead of recaps.
But that only works if a person is still doing the interpreting.
AI can tell me that a competitor changed its pricing page. It cannot decide by itself whether that change should worry me, whether it matters at all, or whether it creates an opportunity elsewhere.
That is strategy. That is judgment. That still belongs to people.
Every company now has access to many of the same AI tools. Fewer companies have people who know which questions to ask and how to act on the answers.
If you want a second set of eyes on what your competitors’ moves actually mean, I am always open to that conversation. No pitch. Just a practical discussion about what is changing, where you may be exposed, and where there may be an opening.
Your competitors may already be using AI to study your next move.
The real question is whether you are using it to study theirs, or still waiting for Friday’s report to tell you what already happened.
For help turning competitor activity into practical insights and next steps, reach Lori at lberson@bersondeanstevens.com or schedule a complimentary call.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
by Lori Berson | Aug 12, 2026 | AI, artificial intelligence, Marketing, marketing technology
Key Takeaways
- AI use is already widespread in marketing and is growing quickly among organizations. Individual AI productivity is far more common than true workflow automation.
- The best starting point is a business bottleneck, not an AI tool.
- Poor processes should be fixed before they are automated.
- AI performance depends on good data, clear rules, ownership, training, and human review.
- Not every task should be automated.
- Start with one high-value, manageable workflow.
- Establish a baseline, measure the outcome, and expand only after the workflow proves useful.
- The long-term advantage will not come from access to AI. It will come from how well the company applies it.
AI adoption is no longer the issue I’m most concerned about. What concerns me is how many companies are using AI without knowing whether it is actually improving the business.
Employees are drafting emails, researching competitors, summarizing meetings, creating content, analyzing information, and experimenting with AI features inside the software they already use. That is progress.
But there is a big difference between using AI and building a better business with AI.
Recent research shows that AI adoption is already widespread. Salesforce’s global survey of 4,850 marketing decision-makers found that 75% of marketing organizations were either experimenting with or had fully implemented AI. High-performing marketing teams were 2.5 times more likely than underperforming teams to have fully integrated it.
A government census revealed small businesses are moving in the same direction. SMB AI use shows that employees are increasingly using AI for writing, research, marketing, customer-facing work, and recurring administrative tasks. Yet according to the U.S. Chamber of Commerce Foundation 2026 study, only 6% of small-business workers report using AI to automate workflows with minimal human involvement.
That is the gap I think business leaders should be paying attention to.
The next stage of AI is not getting employees to try it. It is about figuring out where AI can improve how the company actually works.
Using AI Is Not the Same as Integrating AI
Most companies did not begin using AI with a formal strategy. Someone started using ChatGPT. Someone else began using an AI feature inside HubSpot, Salesforce, Microsoft, Adobe, Google, or another platform.
Marketing used it to create content. Sales used it for research and follow-up. Employees began using it to summarize meetings, review documents, or brainstorm ideas. That experimentation has value. It helps people learn what AI can and cannot do. But experimentation eventually reaches a limit.
The U.S. Chamber of Commerce research illustrates that clearly. Among small-business workers using AI, 64% primarily use it for individual productivity, while only 6% use it for workflow automation with minimal human involvement.
The SMB research illustrates that clearly. Among small-business workers using AI, 64% primarily use it for individual productivity, while only 6% use it for workflow automation with minimal human involvement.
Marketing shows the same pattern. AI is now being used for content optimization, content creation, ideation, workflow automation, social strategy, data analysis, and personalization. But implementation maturity, data quality, training, governance, and trust remain significant barriers.
That tells me: The technology is becoming easier. The business application is still the hard part.
Start With the Bottleneck, Not the AI Tool
When business leaders talk to me about AI, the conversation often begins with software.
- Should we use ChatGPT or Claude?
- Do we need AI agents?
- What can we automate?
- Should we connect AI to our CRM?
Those are reasonable questions. But they are usually not the first questions I would ask.
A better starting point: Where is your company losing time, money, accuracy, responsiveness, or opportunity today?
AI is most useful when it solves an existing business problem. For example, a marketing team might be spending too much time:
- Creating versions of similar emails or campaigns.
- Searching for information across documents and systems.
- Repurposing content.
- Preparing campaign reports.
- Updating CRM records.
- Reviewing work for errors or missing information.
- Researching prospects or competitors.
- Following up after meetings.
- Answering the same internal questions repeatedly.
Those are not AI problems. They are business problems that AI may be able to help solve. That distinction matters because companies sometimes buy an AI tool first and then search for a reason to use it.
I recommend doing the opposite. Find the friction first.
Why Companies Get Stuck
The research points to several reasons why businesses struggle to move from experimentation to measurable results.
1. Employees Know How to Use AI, But Not How to Use It Effectively.
Marketers are already using AI, but training has not kept pace. The research shows that 67% of marketers cite a lack of training as a barrier to AI adoption. Other barriers include a lack of AI strategy, skills, ownership, and governance.
This is why I do not think another general “how to prompt ChatGPT” seminar is enough. Employees need training tied to their actual work.
- A marketer needs to understand how AI can support campaign development, content review, segmentation, analysis, and reporting.
- A salesperson may need help with prospect research, follow-up, proposal preparation, and CRM updates.
- A business leader needs to understand prioritization, ROI, risk, implementation, and where human oversight is required.
The real question is not: How do we teach people to use AI?
It is: How should AI change the way this job gets done?
2. Companies Try to Automate Processes That Are Already Unclear
This is one of the biggest mistakes I see.
If a workflow is inconsistent before AI, automation can simply make the inconsistency happen faster.
Consider lead follow-up. Before automating it, the company needs to define:
- What makes a lead qualified?
- Who owns the lead?
- How quickly should someone respond?
- What information is required?
- What happens when information is missing?
- When does a person need to intervene?
- What counts as a completed handoff?
If those questions do not have clear answers, AI will not solve the problem.
The SMB research supports this. Reliable workflow automation requires standardized processes, connected systems, usable data, ownership, testing, and ongoing maintenance. In other words: Do not automate a bad process. Fix the process first.
3. AI Can Only Work with The Information You Give It
This issue becomes especially important in marketing.
AI can help personalize customer communications. But it needs accurate customer information.
It can analyze CRM data. But poor CRM data will produce poor analysis.
It can answer questions from company documents. But only if those documents are current, approved, and accessible.
It can create content quickly. But speed does not help if the content sounds generic, makes unsupported claims, or does not reflect your brand.
Research on marketing AI adoption points to this same problem. Marketers are using AI for increasingly sophisticated applications, but data readiness and trust continue to limit what companies can do with it.
AI implementation is not just a technology project. It is also a data, process, and management project.
4. Nobody Owns The Outcome
Individual AI adoption often happens from the bottom up. Employees discover a tool and begin using it. That’s easy.
Operational AI requires someone to take responsibility for the result. Leadership needs to decide:
- Which AI opportunities are worth pursuing.
- Which tools are approved.
- What information employees can use.
- Where human review is required.
- What success looks like.
- Who owns the workflow.
- How results will be measured.
- When a workflow should be expanded or stopped.
Without that structure, companies can end up with plenty of AI activity but very little business improvement.
The Goal Should Not Be to Automate Everything
There is a lot of pressure right now to automate as much as possible. I think that is the wrong objective. The better question is:
Which parts of the work should AI handle, and which parts become more valuable when people handle them?
AI is especially useful for repetitive, information-heavy, and data-driven work. It can:
- Review large amounts of information.
- Generate first drafts.
- Summarize content.
- Compare documents.
- Find patterns.
- Categorize information.
- Execute well-defined steps quickly.
- Assist with analysis and decision support.
Humans remain essential for strategy, judgment, creativity, context, relationships, accountability, and decisions where the consequences matter. That balance has been central to how I think about AI.
I have used the idea of treating AI almost like an additional FTE. But I think there is an important condition attached to that idea. An AI “employee” still needs a job description, approved information, processes, supervision, quality standards, and performance measures.
You would not hire an employee, give that person access to everything, provide no training, establish no procedures, and assume productivity would improve. Yet that is close to how some companies are approaching AI.
Don’t Boil The Ocean, Start With One Workflow
I recommend choosing one workflow where there is a clear business problem. Then work through these questions.
What happens today?
Document the current process. Do not assume everyone follows the same steps.
Where is the friction?
Look for:
- Repetitive work.
- Delays.
- Errors.
- Rework.
- Poor access to information.
- Inconsistent follow-up.
- Unnecessary manual steps.
- Bottlenecks that depend on one person.
What should improve?
Define the outcome before selecting the technology. That might mean:
- Reducing a four-hour task to one hour.
- Shortening response time.
- Improving accuracy.
- Reducing repetitive work.
- Increasing follow-up consistency.
- Launching campaigns faster.
- Giving employees more time for higher-value work.
Which steps could AI assist with?
Not every part of the workflow needs AI. Sometimes conventional automation is better. Sometimes the process simply needs to be redesigned.
Where is human judgment required?
Create deliberate checkpoints for review and approval. Human oversight should not be an afterthought.
How will you measure the result?
Establish a baseline before making the change. For marketing, that might include:
- Production time.
- Campaign launch time.
- Conversion.
- Engagement.
- Cost per lead.
- Pipeline contribution.
- Errors and corrections.
- Rework.
For operational workflows, measures might include:
- Time saved.
- Turnaround time.
- Error rate.
- Customer response time.
- Employee capacity.
- Accuracy.
This Is Why I Start With an AI Assessment
The BersonDeanStevens AI Opportunity Assessment begins with the business rather than the software.
The assessment reviews goals, systems, workflows, constraints, data handling, risk, employee adoption, and opportunities to improve efficiency, accuracy, access to information, and service. Opportunities are then prioritized based on business impact, implementation effort, risk, and readiness.
The result is a practical roadmap that helps answer four questions:
- Where can AI deliver value?
- What should we prioritize?
- What should remain under human control?
- How will we know if it worked?
That is a much more useful outcome than a long list of AI tools.
Assessment Is Only the Beginning
Knowing what to do does not mean it will get done. I think this is going to become one of the larger AI challenges for organizations.
A management team can identify ten good AI ideas in one meeting. That does not mean the business should attempt all ten.
I recommend selecting one high-value, manageable workflow, then building, testing, measuring, and refining it before moving to the next one. That is the thinking behind the BDS AI Concierge Service.
The AI Concierge Service provides hands-on support to select, build, test, implement, and improve one priority AI-assisted workflow at a time. The service includes working sessions, custom workflows, documentation, support, performance measures, and ongoing guidance on where to focus next.
The objective is not simply to make people better at using AI. It is to build a growing set of repeatable workflows that improve the business.
Access to AI Will Not Be the Competitive Advantage
This is the point I think many companies are missing. Your competitors have access to the same AI models you do. They can buy many of the same platforms. Their employees can use many of the same tools. AI itself is becoming widely available. So access is unlikely to remain a meaningful competitive advantage.
A company that improves its processes, organizes its knowledge, cleans up its data, trains employees, establishes safeguards, and deliberately incorporates AI into high-value work can become faster, more consistent, and more capable.
A company that simply gives everyone an AI account may produce more work without producing better results. That is the distinction I would focus on now.
The first stage of AI adoption was experimentation. The next stage is operationalization. And that takes more than a prompt.
For help turning AI opportunities into practical workflows and measurable business results, reach Lori at lberson@bersondeanstevens.com or schedule a complimentary call.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
by Lori Berson | Jul 16, 2026 | Branding, Creative Services, Design, Marketing, Marketing Strategy
Key Takeaways
- AI has become table stakes in creative production, not a differentiator. Salesforce reports that 75 percent of marketers are using AI to help scale personalization.
- AI-generated design often looks generic because of vague prompts and missing creative direction, not simply because the tool is incapable.
- Audiences are starting to recognize and reject content that feels overly automated or machine-made.
- Brands such as Equinox and Dollar Shave Club are already building campaigns around the cultural tension surrounding AI-generated advertising.
- Strategy must come before AI touches the work. Otherwise, the fastest tool in the world simply produces forgettable content faster.
- Results support a strategy-first approach. One client’s podcast generated more than twice as many leads as any other content format the company had used.
- Hiring senior creative talent is not a rejection of AI. It combines AI’s production speed with the human judgment it cannot generate independently.
Open five competitor websites in a row right now. You will likely see the same headline fonts, the same gradient background, and the same stock illustrations and photos.
You have seen it. So has everyone else.
That is partly because teams are entering similar prompts into the same handful of AI tools, which were trained on many of the same design patterns.
This is no longer a coincidence. It is the default output.
What AI Actually Does Well
It earns its keep through speed and volume. It can produce first-draft layouts, resize assets across 10 platforms, and generate a dozen headline variations in an afternoon instead of a week.
One creative team recently built a full year of campaign imagery from a single photo shoot using AI. That unlocked production capacity that would have been too expensive to staff otherwise.
That is a real advantage. No one argues that AI has not earned a place in the production process.
What AI Does Not Do Well
Researchers examining why so many AI-built websites look identical have repeatedly found the same root causes: vague prompts, no layout structure, few meaningful design constraints, and no clear point of view behind the request.
The tool did not fail. It did exactly what a generic instruction asked it to do. Generic instructions produce generic output. That is not a bug you can patch. It is the nature of the tool.
Unfortunately, when every team uses the same AI tools, the results start to look the same. AI has real limits when it comes to the work that differentiates a brand, because people using the same tools often receive similar suggestions.
Salesforce’s latest State of Marketing research found that 75 percent of marketers are using AI to help scale personalization. When three out of four marketing teams have access to similar tools, simply using AI is no longer a competitive advantage.
It is table stakes.
Audiences have started to notice, too.
Brands such as Equinox and Dollar Shave Club are now building campaigns around the unease and absurdity surrounding AI-generated advertising. Equinox contrasted surreal AI imagery with photographs of real people. Dollar Shave Club used AI to make corporate overreliance on the technology part of the joke.
The two campaigns took different approaches, but both depended on the same assumption: audiences already recognize content that feels overly automated, artificial, or machine-made…which is worth taking seriously.
What once made marketing feel fresh can now look like a red flag when AI is the only force behind the work.
I saw the same pattern up close while working on a project for a nationwide nontraditional business lender.
Asset-based lending is a complicated and unglamorous product to explain. Unfortunately, the most technically accurate explanations often alienate the business owners who most need to understand it.
Before AI touched a single word, we developed the strategy. We determined how to explain complex lending terms in plain language for the specific audience the client serves. Only after that strategy was approved did our copywriter create the six scripts. AI then turned the copy into voice and the voice into finished audio. Production went from weeks to hours.
But AI did not, and could not, decide what needed to be said, who needed to hear it, or how the client should sound.
The newest episode already has more total downloads than most of the episodes that came before it, despite having spent the least amount of time online. That is the kind of growth curve you see when an audience understands what it is hearing and returns for the next episode. Across six episodes, the podcast generated more than twice as many leads as any other content marketing format the client had used previously.
The strategic decisions came first. That is why the finished podcasts sounded like this client rather than every other lender quietly running the same topics through the same tools.
This is the real case for hiring creative talent instead of running your brand through a prompt box alone. It is not because AI is bad. It is because AI is strongest at the part that was never your real differentiator: execution.
AI has no meaningful opinion about the part that matters most:
- What are you trying to say?
- Who are you trying to reach?
- Why should your version be the one people remember?
A senior creative strategist has something no model can provide: judgment developed through experience. They have seen what worked, what failed, and what looked promising but produced no meaningful result across different industries, audiences, and business situations.
The honest argument is not, “Hire a human instead of AI.” It is, “Hire a human who knows how to use AI as leverage, not as a substitute for a point of view.”
That is a smaller and more focused investment than building a full internal department. It is also a very different bet from buying another software subscription. Everyone has access to the same tools now. Access was never going to remain an advantage.
The question is not whether your team uses AI. The question is whether anyone on your team is making the critical decisions that a model cannot make for you.
Ready to find out how a senior-led creative strategy team can help? Schedule a no-cost call with Lori. No pitch. Just a real conversation about what you’re trying to build.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
by Lori Berson | Jun 16, 2026 | Branding, Creative Services, Design, Marketing, Marketing Strategy
Key Takeaways
- Large agency size often means more layers and less access to the senior talent you actually need.
- Small agencies offer direct accountability, faster execution, and senior-level involvement on every engagement.
- Generic, forgettable creative isn’t a design problem; it’s a strategy problem.
- Long-term client relationships are built on trust, follow-through, and results, not just deliverables.
- A 34% sales lift and a 14-year client relationship started with one question: “Will you still be here?”
There’s a conversation I’ve had more times than I can count. It usually starts the same way: a new prospect sits across from me…sometimes in person, sometimes on a Zoom call, and within the first five minutes, they say some version of this: “Our last agency was a disaster. I’m honestly not sure I trust agencies anymore.”
What comes next is rarely surprising. Slow turnarounds. Generic creative. Account managers who promised the moon and delivered very little. And then, at some point, the agency simply stopped responding. As if the relationship had never existed.
I heard this story again a few years ago from the CEO of a global product manufacturer. A company that sells everything from closet organizers to specialty products around the world. He’d hired a large agency to rebrand and redesign his entire product line. What he got back was work that was technically competent and utterly forgettable. Packaging that didn’t move product. Creative that no one remembered. And eventually, silence.
When he found BersonDeanStevens, his first question wasn’t about our portfolio. It was this: “Will you still be here six months from now?”
That question tells you everything about what large agencies get wrong.
The Ratio Nobody Talks About
If you’ve worked on the brand side of an agency relationship, you already know this dynamic. The client team is almost always small. The agency team far outnumbers it, sometimes at a ratio of 10 to 1 or higher. On paper, that sounds like firepower. In practice, it means more people standing between the problem and the people who can actually solve it.
A large team doesn’t produce more progress. It produces more distance.
The real marketing talent hasn’t left the industry. It’s left the large holding companies. And it’s rebuilding in founder-led, creative-driven agencies that are smaller by design, staffed by people who’ve spent decades running large global brands, navigating boardrooms, legal teams, corporate politics, and the specific pressure that lands on a CMO’s desk every Monday morning. They know what works. More importantly, they know what doesn’t.
This isn’t a consolation prize for clients who can’t afford the big shops. It’s a better model.
Big Doesn’t Mean Better
There’s a persistent myth in marketing that agency size equals agency capability. More people, more resources, more firepower. What it actually means, more often than not, is more layers, more hand-offs, more distance between the senior talent who sold the account and the junior staff quietly doing the work.
You pay for overhead that has nothing to do with your brand. You wait behind bigger accounts. And the people you met in the pitch? You’ll be lucky to see them twice a year.
At BDS, when you hire us, you get a senior team with decades of experience on your account, doing your work, every week. No junior layer running the show while the principals collect the retainer. No hand-offs. No disappearing acts.
What Happened When We Got to Work
For our global manufacturer client, we started where we always start: with the problem behind the problem. The old packaging wasn’t just bland; it wasn’t selling. It wasn’t communicating product value clearly enough to move SKUs off shelves or win new contracts. That’s a strategy failure, not a design failure. The look was the symptom.
We rebuilt the brand from the foundation. New packaging system. Cohesive visual identity across the entire product line. Creative that was built to sell.
The results didn’t take long. Branded packaging sales increased by more than 34%. Private label business grew. Military contracts followed. The rebrand opened doors that the old creative had quietly been keeping shut.
And the client? He didn’t leave after the project wrapped. He stayed for over fourteen years, through a second full rebrand. That’s not a vendor relationship. That’s a partnership.
What Small Agencies Actually Deliver
If you’re evaluating agencies right now, or quietly wondering if the one you have is giving you everything you’re paying for, here’s what the research and 27 years of experience tell us small agencies consistently do better:
- Direct senior access. The strategist, the creative director, the person accountable for results – you can reach them today. Not through three layers of account management.
- Genuine accountability. Small agencies don’t have the cushion to coast. If the work doesn’t perform, everyone feels it. That keeps the standard high.
- Faster turnarounds. Fewer approval layers mean fewer delays. Decisions get made by people who understand the full picture.
- Continuity. You’re not reassigned when an account lead changes jobs. The brand’s institutional knowledge doesn’t walk out the door with them.
- Creative that earns its keep. Small agencies can’t hide behind production volume. Every deliverable has to work.
The Question Worth Asking
If you’re paying an agency right now and the results feel flat, you already know something is wrong. The question isn’t whether to make a change. It’s why you haven’t yet.
Small is not a step down. For the right client, it’s the better answer.
Ready to find out what a senior-led, results-accountable agency actually looks like? Schedule a no-cost call with Lori. No pitch. No junior associate. Just a real conversation about what you’re trying to build.
BersonDeanStevens (BDS) has developed creative, results-driven marketing strategies, content, campaigns, and programs for over 27 years – with AI incorporated where it adds efficiency and lifts results. Whether you need a fractional CMO, assistance for an overloaded team, or strategic counsel from time to time, BDS is your go-to resource. Client list.
