What Puppies Can Teach Us About AI

Companies rushing to adopt generative AI are lured by productivity promises. Yet many discover that having these powerful tools doesn't automatically lead to better results. Like that puppy, AI needs proper training and guidance to become truly helpful.

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When Promise Meets Reality

Remember when spell-check promised perfect writing for everyone? AI tools can feel similar. A marketer might ask AI to write an article, receiving something that looks professional, but contains made-up facts or misses crucial nuances within the content.

This gap exists because AI lacks the judgment that comes from human experience. While it excels at processing vast amounts of information and generating content, it can't inherently tell whether its output serves your business goals. It won’t fact-check unless prompted, nor will it reflect on whether the information is relevant to your audience.

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Language Models Might Be Nerdy – But Context Is What Matters

Successful AI adoption doesn’t necessarily hinge on technical expertise. Rather than AI scientists or deep knowledge of language models, organizations who are just starting their journey using Generative AI need people who can guide these tools effectively within specific contexts.

Who do we turn to for expertise on how to guide our new puppy’s learning? The value of the professional dog trainers comes not from expertise in, say, canine genetics, but from practical knowledge of shaping desired behaviors. Similarly, valuable AI skills center on:

• Crafting questions that yield useful answers

• Identifying misaligned or incorrect output

• Applying context to make content meaningful

• Refining and improving AI suggestions

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Common Challenges with Gen AI

Different teams face unique struggles with AI implementation:

• Marketing teams work to preserve authentic brand voice while using AI for content creation.  

• Customer service departments are seeking to balance efficiency with genuine human connection.  

• Regulated industries must ensure AI use aligns with compliance requirements.

These challenges stem from integrating AI capabilities with human expertise and business needs, not from technical limitations.

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Creating Strong Human-AI Teams

Effective AI use demands new approaches to training and development. Teams must learn:

• Critical evaluation becomes essential. People need practice spotting AI-generated content that seems plausible but contains subtle errors or misalignments with goals.

• Context shapes everything. Generic AI prompts rarely deliver optimal results. Teams succeed by guiding tools with specific knowledge of their industry, audience, and objectives.

• Human qualities matter a lot. As AI handles routine tasks, skills like empathy, strategic thinking, and creative problem-solving grow increasingly valuable.

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Moving Forward

AI works best when humans are there to keep a watchful eye on output, and when those standards can be reused and reinforced with every chat, source document, prompt, and edit. Some of the most critical topics in AI skilling that we’ve seen:

• Writing clear prompts aligned with objectives

• Reviewing AI output for accuracy and relevance

• Identifying appropriate use cases

• Maintaining creativity and connection in AI-assisted work

• Documenting and constantly revising guidelines that can be used in concert with prompting

• Maintaining critical thinking in both review and interaction with AI tools

Organizations thrive not by adopting AI fastest, but by working with it most effectively. Like that puppy, with proper guidance, AI becomes an invaluable partner - shaped by the expertise of those who train it.

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Want help building effective human-AI partnerships in your organization? Let's talk about how we can help you develop a people-first AI implementation strategy.