Introduction
In this article, we provide an overview of the importance of understanding the variety of AI platforms and tools that can help you stay competitive in your industry. We will explore the benefits, how to approach implementation, the role of AI in text analytics and its potential to replace traditional coding processes. Finally, we will share some practical examples of AI in action and resources we’ve found beneficial for further learning.
The Rise of AI
As an organization that has deployed our own custom generative AI platform in-house, we’ve learned how critical it is to stay on top of news and shifts in our industry daily because that’s how fast the industry is changing. Platforms like Gemini, OpenAI, Microsoft Copilot, and others are constantly launching new features and innovations. Your IT team should strive to stay informed about the latest AI developments and how to benefit from those tools that are most relevant to your organization. From there, you can make informed decisions about incorporating AI into your workflows.
Making the Right Choices
We have found through our client engagements that while an organization feels it is ready for AI, not every area within it may be ready for AI implementation, and that’s okay. It’s important to carefully evaluate multiple AI solutions to determine which are the right fit for your specific needs, or if they are at all. When selecting an AI platform, we consider factors such as cost, feasibility, and the potential impact it will have on your business and processes. As you venture into AI research, we suggest that you focus on areas where an AI solution can provide the most value. For example, AI-based tools combined with RPA can be used to automate tasks like sales pitch analysis and proposal generation, reducing the time and effort currently required for these tasks. However, discrete problems that may not have corresponding data or low process maturity may be better suited for other problem-solving tools. Steer your focus to AI solutions that solve text-heavy, data-rich and highly manual processes and ensure these solutions such as robotic processing automation (RPA) and machine learning (ML) are appropriately used in this ecosystem. Bear in mind, that not every problem is appropriate for an AI solution.
Replacing Traditional Coding Processes
One area we have found where AI has a significant impact is in text analytics. While platforms like Envivo and WordStat have traditionally been used for coding and analyzing language and text, there are AI platforms like Gemini that can also perform similar tasks, providing numerical outputs that can be used for scenario cluster analysis. While AI platforms cannot completely replace the coding process, they can certainly enhance it and provide more efficient and accurate results, saving your organization time and money. For example, leveraging these platforms to encode transcripts from a meeting recording, then identify process-related pain points and even perform cluster analysis on root causes, is all possible.
Practical Examples of AI in Action
AI is fast becoming the new norm for business efficiency and competitiveness. We believe that once you start recognizing its presence, you’ll begin to see it employed everywhere. Here are a few practical examples of AI at work:
- Automated Car Systems: We all benefit today from the latest AI-powered tools in our vehicles from cruise control systems to sensors and advanced algorithms that now detect lane deviations, apply braking systems and adjust the vehicle’s position to improve safety features and reduce the risk of accidents.
- Personalized Coupons and Targeting Marketing: Grocery retailers like Kroger use AI to tailor coupons based on individual preferences and purchase history. By analyzing customer data, AI algorithms generate personalized offers to increase customer satisfaction and drive more sales. We are sure you have experienced this firsthand.
- Hardware Store Photo Tool: The Home Depot has a photo tool that allows customers to take a picture of a part they need. It then identifies the part, checks its availability in nearby stores, and provides directions to find it. This saves the customer’s time in store, and frustration due to the lack of available staff and overall improves the customer experience and likelihood of sales.
We also know firsthand the benefits of employing AI tools in our growing boutique consultancy. For instance, we employed AI in many areas across our organization to expedite the development of customized SOP’s, job aids, identification of pain points, improved training and onboarding, proposal and contract management processes, and better risk management. For our clients, we can quickly identify gaps in their performance against industry standards through our enhanced benchmarking tool. From these few applications, we have seen a dramatic improvement in efficiency leaving us to focus more on client solutions and implementation – where we excel!
Learning and Exploring AI Tools
We encourage you to learn more about AI tools and platforms and recommend the following resources:
- Download ChatGPT 3.5 from OpenAI‘s platform and start experimenting with it.
- Explore YouTube tutorials and online forums to learn how to integrate AI tools like Python and ChatGPT.
- Look for step-by-step guidance on using AI platforms and creating custom algorithms for specific tasks you want to focus on.
AI tools can be used to ask questions, generate code, and provide guidance in various programming languages. They can be a valuable companion in navigating the world of AI and automation. Note that there is an art and science to optimizing your Chat responses, largely predicated on how you ask and state your questions. Many resources are available on the web by researching and exploring “ChatGPT prompts”.
Choosing the Right Projects
When assisting a client who is interested in AI applications, we first look at the organization’s goals and priorities. This allows us to choose the right projects that require or would benefit dramatically from an AI solution. For those wishing to do this in-house, as we mentioned earlier, it’s important to start small, focus on cybersecurity, and create a closed-loop environment for experimentation. The reason behind this is that your first experience with AI will also be a learning experience, so it is best to apply it to small manageable projects, from which you can build confidence in your AI capabilities. Choosing smaller projects can also mitigate risks as you learn, select and employ AI applications, and manipulate where required to produce the objectives you set out to achieve. We have found that successful organizations adopting AI and automation technologies focus on driving business results and improving customer satisfaction. While it’s easy to get enamoured with AI ‘shiny objects’, your goal should be to enhance operational efficiency and improve the delivery of the right products/services to your customers at the right time and cost.
Conclusion
We know from experience that there is a definite learning curve for those wishing to adopt AI solutions to evolve their business operations. We also believe that this should be a priority for every business if they wish to grow and improve their ability to compete. As you begin to explore AI and the opportunities it presents, remember to keep the end game in mind by prioritizing key business results and how you can achieve them through AI adoption. We encourage you to reach out to our AI professionals if you would like further direction or need assistance to fast track your progress. Or, we can work with you to select the best AI tools and help you to achieve faster results by integrating them into your systems.
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