Brands using AI to write RFPs are a red flag. These documents are easy to spot and lack the specific, human insight needed for a quality response. Briefs should come directly from senior decision-makers to clearly articulate the business's actual needs.

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Using AI to generate content without adding human context simply transfers the intellectual effort to the recipient. This creates rework, confusion, and can damage professional relationships, explaining the low ROI seen in many AI initiatives.

Avoid using AI to create sales outreach from scratch ('black pen'). Instead, use it as an editor ('red pen'). Apply the 10-80-10 rule: 10% human-led prompting, 80% AI-driven task execution, and a final 10% human refinement. This maintains quality while boosting efficiency.

To analyze brand alignment accurately, AI must be trained on a company's specific, proprietary brand content—its promise, intended expression, and examples. This builds a unique corpus of understanding, enabling the AI to identify subtle deviations from the desired brand voice, a task impossible with generic sentiment analysis.

AI-generated text often falls back on clichés and recognizable patterns. To combat this, create a master prompt that includes a list of banned words (e.g., "innovative," "excited to") and common LLM phrases. This forces the model to generate more specific, higher-impact, and human-like copy.

As AI floods the internet with generic content, consumers are growing skeptical of corporate voices. This is accelerating a shift in trust from faceless brands to authentic individuals and creators. B2B marketing must adapt by building strategies around these human-led channels, which now often outperform traditional brand-led marketing.

While AI offers efficiency gains, its true marketing potential is as a collaborative partner. This "designed intelligence" approach uses AI for scale and data processing, freeing humans for creativity, connection, and building empathetic customer experiences, thus amplifying human imagination rather than just automating tasks.

AI cannot replicate your lived experience, personal experiments, or unique perspective. To make your content "AI-proof," lead with your own stories, data, and case studies. Sharing screenshots, income reports, and personal struggles creates content that AI can't remix, making your voice irreplaceable.

Many companies fail with AI prospecting because their outputs are generic. The key to success isn't the AI tool but the quality of the data fed into it and relentless prompt iteration. It took the speakers six months—not six weeks—to outperform traditional methods, highlighting the need for patience and deep customization with sales team feedback.

AI should not be the starting point for creation, as that leads to generic, spam-like output. Instead, begin with a distinct human point of view and strategy. Then, leverage AI to scale that unique perspective, personalize it with data, and amplify its distribution.

AI outbound tools pull from the same databases, hitting the same people with similar messages. To stand out, go fully manual. Research individuals, send unique, short messages, and target people not in common databases. This "back door" approach is more effective for high-value deals.

AI-Generated Pitch Briefs Lack Nuance and Signal a Disengaged Client | RiffOn