The power of generative AI in today’s world is undeniable. People use it for menial tasks, marketers consult it for content creation, and companies employ models and systems for operational needs. 

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Generative AI (genAI) supports a business’s performance and accelerates goals, from simplifying employees’ tasks to improving operational efficiency to running a customer service chatbot. Nevertheless, every small and medium-sized business (SMB) must analyze its preparedness when adopting it. 

Is It Worth Implementing GenAI in Your Business Strategy?

For many companies, generative AI plays a critical role in their business operations. One study found that 65% of respondents use genAI in their organizations. Indeed, generative AI can offer a vast range of benefits for businesses, including:

  • Seamless customer support: Implementing genAI in chatbots and virtual assistants allows businesses to provide instant, sophisticated natural responses to questions and issues, which improves overall customer satisfaction.
  • Insightful data analytics: By using genAI to analyze large datasets, companies can uncover patterns and insights that can help them improve their business strategies and stay competitive.
  • Enhanced SEO strategy: GenAI can be an invaluable tool in SEO services by providing content recommendations based on recommended keyword targets, analyses of competitor content and quick identification of ways to improve existing pages.
  • Impressive content creation: Businesses can automate routine content creation tasks like summaries and meta descriptions, freeing up time for professionals to focus on more creative tasks.

With the vast number of benefits, it may seem like a given to incorporate generative AI into your business practices. However, AI’s many use cases are only beneficial if implemented well, meaning businesses must first assess whether they’re in fact ready to bring generative AI into their employees’ routines.

Is Your Business Ready for GenAI? 5 Considerations

After deciding if genAI is right for your SMB, assessing your readiness for implementation requires careful thought and updates across resources. Here are some aspects to consider when determining if your company is prepared.

1. Data Preparedness

You may have organized and implemented data alignment since the start of your business, but data preparedness is vital to generative AI. 

Many organizations prioritize data readiness, with 75% enhancing tech investments in information management to adopt generative AI. About 55% avoid using it due to data-related issues. 

You need a clear and comprehensive strategy that aligns with the vision and allows seamless access to and integration of data from multiple sources within the company. This would help you achieve better results with generative AI models. 

2. Information Quality and Governance 

Are you ready and confident in the accuracy of the data generated and the security of those provided? 

Studies indicate that large language models (LLM), responsible for the algorithmic platforms that create generative AI tools, are not as transparent as they should be. One study found that the transparency score was only 37% among 10 LLMs. Another discovered that 59% of executives are concerned that generative AI could put sensitive data at risk.

However transformative generative AI is to the business landscape, it has limitations in precision and consistency. Many organizations combat this by solidifying data governance to enhance privacy and security. 

3. Talent Availability

Your SMB needs the right talent to optimize generative AI models and systems.  

More than 75% of organizations plan to implement technologies like AI, big data and cloud computing in the next four years. The fastest-growing positions are expected to be tech-related jobs, with AI and machine learning specialists topping the list. This shows the necessity of these talents in organizations looking to adopt generative AI. 

Your business should be ready to hire relevant talent or commit to training and upskilling existing staff for the role.

4. Infrastructure Availability

Generative AI models are becoming more savvy, and the computational demand for efficient ones is becoming less gloomy due to market competition.

Generative AI is predicted to account for only about 34% of the global data center-based computing supply by 2028, even after considering its exponential growth and infrastructure demand.  Even then, an SMB looking to implement it needs sound infrastructure, such as cloud-based tools and higher bandwidth, for training and implementation.

5. Ethical Concerns

The adoption of generative AI is revolutionary but could prove problematic if companies do not exercise proper governance. 

Businesses that work with generative models should be wary of unknown fields where the model is not trained, copyright issues, bias and toxicity, and data leakage. They should also be prepared for hallucinations where outputs could be convincing but false, such as in the Gemini AI controversy.

Before implementing generative AI for your business, ensure you have considered the potential biases you may encounter and are willing to train your personnel to use the models responsibly. 

Navigate the Generative AI Era With Predictive Preparedness

Generative AI is a game changer in how people function and could bring transformational success to an organization. Assessing the preparedness of your SMB is your responsibility as a leader and is key to maximizing the benefits of these models and systems.