In Part 2 of our AI and Business series, Kinetic IT developers Domenic Horner and Daryl Crosbie talk about what you need to consider before implementing AI in your business.
Less than two months after we released our insight, we are analysing the top ways artificial intelligence (AI) is transforming business. However, the AI race continues to progress at lightning speeds. OpenAI released ChatGPT-4, the most advanced system yet. It can generate meal ideas based on what’s in your fridge, create a detailed learning syllabus, and even diagnose medical conditions in animals and humans.
Meanwhile, Microsoft introduced its new 365 CoPilot, an AI assistant for Microsoft 365 applications, and Security Pilot, an AI-powered security analysis tool that processes and responds to threats in minutes. In March, Bill Gates said, “AI is as revolutionary as mobile phones and the Internet”, and it “will help empower people at work, save lives, and improve education”.
However, in response to the full-throttle AI advancement, the Future of Life Institute has started a petition calling on all AI labs to “immediately pause for at least 6 months the training of AI systems more powerful than GPT-4”. The petition has garnered over 22,000 signatures in three weeks, including global industry leaders such as Apple co-founder Steve Wozniak, Tesla CEO Elon Musk, Stability AI CEO Emad Mostaque, and Geometric Intelligence founder Gary Marcus.
The petition does not call for an overall pause on AI development but recommends that AI labs use the pause to develop shared safety protocols for AI development that independent experts audit.
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Should you implement AI in your business?
You’re not alone if you’re considering implementing AI in your business. As AI continues to make waves, more enterprises see it as a vital tool to remain competitive.
A 2024 report by Gartner found that 87% of CEOs agree that AI’s benefits to their business outweigh its risks, and a whopping 75% of organisations believe AI technology will help them enter new ventures.
While AI development is advancing rapidly, it is essential to pause and carefully consider the integration challenges before diving in. Although it promises to boost productivity and efficiency, implementing it in your business can be more complex than anticipated. Integrating these systems requires thorough planning and preparation to ensure success.
We spoke with Kinetic IT developers Domenic Horner and Daryl Crosbie about the key considerations to address before implementing AI in your business to ensure you maximise its benefits.
1. Can AI help your business achieve its goals?
Before implementing AI in your business, the most crucial consideration is whether it aligns with your business strategy and will contribute to achieving your long-term goals.
Senior Applications Developer Domenic Horner says, “Organisations will need to identify the areas where AI can provide the most significant benefits, such as automation, enhanced customer experiences, or data-driven decision-making.”
2. Should you build your own AI software or use existing tools?
Businesses must consider whether the most significant value comes from bespoke AI software or existing tools.
Solutions Developer Daryl Crosbie says, “AI software can be difficult to build as there are many aspects to consider, test and evaluate. You need to consider the model used to train the bot, evaluate the training data, and adjust the model. The most difficult part tends to be acquiring enough diverse data to train the bot. With all this in mind, if existing machine learning software suits your needs, it may be best to test and evaluate this first.”
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3. Do you have the infrastructure and talent to implement AI in your business?
If you’ve ever adopted a new system, tool, or strategy in your business, you already know it can be a lengthy and complex process. The same goes for integrating AI technology. You’ll first need to assess your existing IT infrastructure, including computing power, storage capacity and network security, to determine if it can accommodate AI systems. You may need to consider upgrading your infrastructure or migrating to cloud-based solutions if there are gaps.
While it’s crucial to identify appropriate tools and software to manage and monitor AI solutions, you’ll also need the right people. AI implementation requires skilled teams of engineers and experts with AI and machine learning skills and knowledge.
“You may need to hire new talent, upskill your current workforce or partner with external providers,” says Domenic. “You’ll also need to invest in development and training to stay on top of this rapidly changing technology.”
4. Is the AI technology compatible with your current processes?
Your current IT infrastructure and teams may be well-equipped to implement AI in your business – but will they be compatible with AI technology? You must plan how AI systems integrate with your existing infrastructure, software, and processes.
“Work with your team to identify potential compatibility issues, such as data formats and communication protocols, and address them early on to avoid headaches down the road,” says Daryl. “By designing APIs, adopting standard interfaces, or leveraging middleware solutions, you can achieve a smooth and seamless AI integration.”
5. Is the AI technology scalable?
If you’re doing the work to adopt AI in your business, you also want it to be scalable and adaptable to changing needs. As your business grows, you’ll need your AI systems to scale easily to handle increasing data volumes and users and expand across business units or regions.
“Flexible, modular, cloud-based AI solutions are best for scalability,” says Domenic.
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6. What data was used to train the AI system?
Not all AI tools are created equally. AI systems rely heavily on data for training and functioning, so it’s crucial to have high-quality, diverse data to train AI models effectively. This is one of the most significant challenges in implementing AI in your business, as obtaining and cleaning data can be time-consuming and expensive. You’ll need to examine the data’s quality, quantity, and variety and check for data accuracy, consistency, and relevance to ensure it’s suitable for AI implementation.
“The data used to train the AI model is very important, as it needs to be as diverse as possible,” says Daryl. “If it contains biases, the algorithm will likely hold this bias in its results. Numerous models can be used to build AI applications. Each model can have its pros and cons regarding the data being used. Some machine learning models can produce data that can be difficult to interpret, so depending on the type of data you wish to work with and your needs for the data, choosing the right model should be considered as it can be essential.”
7. How effective is AI technology in your business?
AI tools are powerful, efficient, and entertaining, but they are not always the right fit. AI tools aren’t infallible and can make mistakes—just like humans.
Domenic says, “AI-powered tools like the language model ChatGPT can help write articles or work instructions, provide highly technical answers to questions, and triage IT incidents. However, there are downsides to this, as the accuracy of the answers is not validated by any human, and they can and sometimes do, contain incorrect information.”
One way to overcome this is by starting with small pilot projects to test the effectiveness of AI solutions and their integration into your systems. Your teams can monitor the results, gather feedback, and identify areas for improvement. This will help you refine the AI models, minimise risks, and maximise the benefits of your AI tools and systems.
8. How high are your expectations when implementing AI in your business?
An iterative integration process will also help manage business expectations around AI. While AI has made extraordinary advancements in the last few years (and months!), many AI tools are still finding their feet regarding capabilities.
“The technology in AI and machine learning is advancing at a very rapid pace, and there are more and more use-cases being developed and proven with each advancement”, says Domenic. “However, models like ChatGPT are still very fresh, and there have not been many implementations of this technology from which to learn.”
Set realistic expectations if you’re ready to implement AI tools in your business. AI is not a magical cure-all and can’t do everything and fix every problem. AI has already shown itself to be a powerful tool for solving complex problems and improving efficiency. As the technology advances, the possibilities for positive impact will become almost limitless.
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9. What are the financial costs of implementing AI in your business?
Like any new technology, AI tools and systems can be expensive.
Daryl says, “Due to the cost of integrating and running AI to perform tasks, businesses must carefully evaluate the return on investment. However, most implementations of AI stand to significantly reduce costs to the business for the long term.”
Domenic agrees: “AI-powered technologies can automate repetitive, time-consuming tasks, freeing employees to focus on higher-level, more creative tasks, leading to improved efficiency and productivity for businesses. For example, you can hand the job to an AI-powered customer chatbot instead of using human talent to answer simple customer queries. They’ll get it done faster and free up time for people to manage more complex tasks.
When considering the total cost of implementing AI in your business, consider the costs of hardware, software, training, talent acquisition and ongoing maintenance. You’ll also need to compare the costs with the anticipated return on investment (ROI) to ensure the project is financially viable. Many businesses discover that AI tools can vastly reduce time and resources, making it a more economical option.
10. What are the ethical implications of using AI?
While AI can revolutionise every industry, it’s essential to acknowledge and mitigate the risks and ethical concerns associated with developing this technology and implementing it in your business.
“There are some ethical concerns as the AI must be trained using publicly available information which has the potential to contain Licensed or Protected information,” says Domenic. “There are also concerns about privacy, security, accountability, transparency, and potential biases. As AI becomes more widely adopted, we expect increased demand for regulation and standards to ensure that AI is developed and used responsibly and ethically.”
With greater awareness and education, organisations will be better placed to navigate the challenges and opportunities of AI.
11. Is the broader business prepared to adopt AI?
Implementing AI in your business can result in significant organisational and cultural shifts. A change management strategy can help employees adapt to new tools, processes, and working methods. You’ll need to develop communication, training, and support programs and be prepared to address concerns and manage expectations throughout the AI integration.
And if you need assistance developing all these strategies, programs, and communications, AI can help—just ask ChatGPT.
