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AI Content Adoption Shouldn’t Be Hard

AI Content Adoption Shouldn’t Be Hard

AI Strategy, Custom Language Models

You’re Right, Using AI Shouldn’t Be This Hard!

Creating personalized, relevant content is and has been a challenge for marketers. Statistics reflect these challenges: 

  • 57% struggle with aligning content to their audience’s expectations, 
  • 54% find maintaining content consistency and differentiation significant hurdles. 

Ironically, AI’s promises are perceived to mirror the complexity of the very solutions it’s intended to benefit. The promise of AI’s efficiency and efficacy capabilities has not yet been realized.

The art of ‘prompt engineering’—an endeavor at times as cryptic as it is technical—remains misunderstood as the necessary approach to use AI.

Any member of an organization should be able to use simple English questions and receive a robust human-quality response from an AI tool.

We hear marketing leaders use the terms “it gives me hives” and “anxiety” to describe their view of GenAI tools. 

Interestingly, this is similar to how leaders a generation earlier described the DOS prompt on early PCs!

One piece of advice to sales and marketing leaders… You’re right; these tools shouldn’t be that hard. #ItsThemNotYou

The question wasn’t whether everyone would have a PC on their desk but rather when it would happen. The same is true with GenAI.

The question then is, how?

Find the use cases that are critical to your company. Is it content creation, sales enablement, competitive intelligence, ABM personalized content, or something else?

Next, find options that your team CAN adopt. Use the lens of usability. 

AI can’t deliver value in efficiency and efficacy if nobody knows how to use the tools!

Symplexity.AI defeats the complexity villain

Symplexity.AI defeats the complexity villain

AI Adoption, AI Strategy, Custom Language Models

Demystifying AI for B2B Sales & Marketing:

Symplexity.AI defeats the complexity villain 

A sinister shadow looms large over the B2B sales and marketing metropolis. No ordinary villain, this adversary possessed a secret decoder ring, a tool that held the power to break through confusion and anxiety fraught by AI transformation.

The promise of AI, with its potential for productivity, efficiency, and effectiveness, seemed an elusive dream, locked away by the convolutions this ring wielded by our villain.

Our superheroine comes to the rescue!

In a decisive act, our hero removed the ring from the villain’s grasp and destroyed it.

Instantly, the veil of complexity was lifted.

Sales and marketing professionals worldwide suddenly found AI’s promises accessible and integral to their success. While fictional, this tale is a powerful metaphor for the actual journey B2B sales and marketing leaders must undertake to harness AI’s capabilities.

The Stark Reality of AI Adoption

Despite AI’s immense potential, integrating it into B2B sales and marketing strategies has been a challenge. When discussing this divide, people point to anxiety and fear. The expectation of seamlessly incorporating AI technologies into daily operations has clashed with the steep “learning cliff” of learning how to interact with these tools.

The decoder ring in our narrative symbolizes the early stage of AI development. Today, users find themselves learning how to conform to tools like ChatGPT rather than finding tools that conform to them.

 

Is it too much to ask? No, it’s what should have already existed.

You should be able to enter a simple English query and get a human-quality response that reflects your brand, voice, differentiation, delivered value, and more.

This gap presents a fundamental obstacle in AI adoption. The intimidation factor, caused by daunting demands on a user, has created a pervasive lack of understanding. This doesn’t need to exist.

As McKinsey highlighted, high-performing sales organizations are twice as likely to incorporate AI into their sales processes, showcasing a direct correlation between AI adoption and performance. Yet, impediments like poor data quality, a shortage of skilled personnel, and a lack of clear strategic direction continue to hinder widespread adoption.

 

You shouldn’t need a decoder ring to use AI tools successfully.

AI should be intuitive, easy to use, and conform to your needs. The talent gap and unnecessarily hard-to-use tools exacerbate the issue. An MIT Sloan Management Review article reveals that a mere 20% of businesses have effectively scaled an AI strategy, attributing this shortfall to a deficiency in the requisite skills to use the tools at hand. Bridging this talent gap or changing tools is essential for leveraging AI’s full potential.

Conclusion: Unveiling the Promise of AI
Our secret decoder ring illustrates the facade that hinders our journey toward AI democratization in B2B sales and marketing. Leaders can unlock AI’s true potential by confronting the tools we select and the data and skill gaps, ensuring strategic alignment, and adopting effective change management practices.

For sales and marketing professionals, this journey involves dismantling AI’s real and perceived complexities to reveal its inherent advantages. In doing so, they enable more informed decision-making, optimize customer experiences, and contribute to democratizing success in the B2B domain.

Prompt Engineering should never have ever been a thing.

Prompt Engineering should never have ever been a thing.

AI Adoption, AI Strategy, Custom Language Models

News Flash:

Superhero Saves Square Peg from Round Hole!

“Prompt Engineering” shouldn’t be a thing. GPTs are the world’s largest encyclopedias. The data is vast, meaning it can tell you about Quantum Mechanics, but it’s also generic, meaning it can’t differentiate the strengths of your solutions from those of your competitors. Because of this, “Prompt Engineering” became a thing. The crux of engineering is getting a tool to do something it was never built to do. Looking at a GPT interface is reminiscent of a DOS prompt on a PC back in the 80s. The word was that everyone would have one of these things on their desk in a few years. Right. The issue is the “learning cliff.” When using a tool is more daunting than the perceived value of the solution… people don’t use them!

GPTs are a consumer interface into a Large Language Model.

It doesn’t know your differentiation and brand voice. You need it to know more.

“Prompt Engineering” became a thing because you’re trying to make it do something it wasn’t designed to do.

GPTs are today’s DOS prompt.

  • According to McKinsey research, Generative AI adoption rates in marketing and sales are at 14%. The pace of AI adoption does not align with its potential advantages. Yet, 75% expect Generative AI to cause significant or disruptive change within three years.
  • Gartner indicates that 34% identify a lack of AI skills and knowledge. A similar 1/3 of companies identify resistance from employees who fear role reduction or elimination as barriers to AI adoption. Additionally, 31% highlighted the need for training and development to upskill and share knowledge as critical issues, identifying major challenges related to understanding, education, confidence, and trust in AI technologies.
  • The Rain Group’s industry research underscored that 50% of respondents reported difficulty keeping up with AI advancements, and 38% felt overwhelmed by the options and use cases. Furthermore, 59% showed concern about inaccurate or misleading information from AI, and 45% were wary of data privacy and security issues, underlining the issues of trust and confidence in these tools.

These statistics reflect real-world challenges in AI adoption. Anxiety, fear, and overwhelm are caused by rapidly advancing technologies that people find difficult to track and understand.

What if we changed the calculus?

Sales and marketing teams should be able to enter a plain English question and receive a human-written quality output from an AI tool. Period.

Prompt Engineering would become unnecessary.

The tools would comport to the user. Not the other way around.

Introducing the Symplexity.AI Studio

Symplexity.AI is like using a PC with Windows rather than DOS.

The tool does what it should without a radical change in user learning and behavior.

Show me how this works!

Symplexity.AI removes the GPTs from the equation, inserts your learning, brand voice, differentiation, and persona needs into the equation, and communicates directly with OpenAI.

This technology was purpose-built to address the gap between AI’s evolving capabilities and the actual adoption rates within sales and marketing teams. Today, your team can interact with AI using simple English questions and get human-written quality responses that reflect your brand.

The perceived complexity, risk, and general lack of foundational AI knowledge among these teams unnecessarily cause anxiety and prevent progress in realizing the benefits of this groundbreaking new technology.

 

The core problems that Symplexity.AI aims to solve involve:

  • Simplifying the perceived complexity and risks believed to be associated with AI.
  • Democratizing the successful application of AI. Our approach to creating Custom Language Models bridges the divide between the potential of AI technology and the current latent adoption inertia. These tools should be easy to use. These tools should adapt to the user, not force users to comport to them.
  • The decision between generic tools that create verbose and unusable responses and the need for education to help employees use them shouldn’t exist.