Every new technology makes waves in the industry but none can match the hype around artificial intelligence. Since its inception in late 2022, ChatGPT has become the talk of the town. From employees to C-suite executives, everyone is using these large language models. Just like every new technology, generative AI also comes with its fair share of shortcomings.
From biases to hallucinations, data security woes to privacy concerns, we have already seen glimpses of all that with generative AI. Even though most businesses are seriously considering generative AI in their organization, these issues serve as a roadblock. How can businesses make the most of this technology without getting into hot waters? By asking some tough questions and answering them before implementing generative AI.
What are these questions? That is exactly what we are going to discuss in this article. In this article, you will learn about six tough questions IT leaders must answer before adopting artificial intelligence.
6 Tough Artificial Intelligence Questions IT Leaders Must Answer
Here are six tough AI questions that IT leaders must answer before implementing the technology in their organization.
Which Business Cases Require AI Implementation?
According to CEO Outlook Pulse, Almost all (99%) of Chief Executive Officers said that they are planning to invest in generative AI. The real question is that are they making the right investments? That is where tying your generative AI investments to your business use case, needs and goals is critical.
Knowing the specific business use case that requires AI implementation can make all the difference. If you know which areas of your business are in dire need of automation and can implement artificial intelligence there, it can lift your entire organization’s productivity, efficiency and revenue.
When you focus on how generative AI can help you solve a particular problem, it will help you look at technology from a whole new perspective. Users can also use the same formula when buying a semi dedicated server or any other technology.
Bill Smith, CIO of State of Alaska, “We are all talking about AI, and there are a lot of expectations and hype around it, but at the same time there’s really this lack of rigor around the use cases that can develop in these hype cycles. So people often come with solutions in mind and not problems to solve. So I’m asking, ‘What specifically are you trying to address?’ because maybe what they need is not AI.”
Which Ideas Will Actually Deliver Business Value?
According to a Business Opportunity of AI report, artificial intelligence delivers 350% return on investment. This means that for every dollar you invest in artificial intelligence, you can get $3.50. What’s even more surprising is that businesses who invested in artificial intelligence managed to get this return on their investment within 14 months
Despite delivering exceptional returns in the fastest time, most businesses are struggling to make the most out of the technology yet. Did you know why? Because they tend to ignore the business value element when implementing generative AI. You don’t want to be spending time, money and effort on projects that don’t deliver business value. Know the business benefits and business value each artificial intelligence projects can bring to the table before
What Goals Do We Want to Achieve With AI Implementation?
If identifying the right business use case and evaluating the business value of AI projects is important then so does understanding the business goals AI can help you achieve. Enterprises must also allocate a budget for artificial intelligence implementation as it is resource intensive. IT leaders should also be able to map out the per dollar value of projects. Can you achieve your desired goals with a limited budget?
Can Our Current Technology Infrastructure Capable of Delivering Results With Artificial Intelligence?
Let’s say, you have ticked all the boxes from business value to business use case. What’s next? The next question you need to ask as an IT leader is is your current technology infrastructure capable of supporting AI technology? If not, do you have the budget to replace your current hardware with the AI supported hardware? Most businesses can afford to make few changes to their technology stack but struggle when it comes to repairing their entire tech stack.
What are the Risks and How We Would Overcome Those Risks?
Probably, the most important but least talked about topic about generative AI is the risk associated with the technology. Due to this, most businesses are unaware about the negative consequences they might have to face after implementing the artificial intelligence technology. How can you protect against a risk when you don’t know that it even exists? That is the problem most businesses are experiencing right now.
Since they are unaware of the risks, they don’t take any steps to mitigate those risks. IT leaders must devise a strategy to curb those risks in order to ensure smoother transition. What steps are you taking to minimize the risk? This will go a long way in protecting your business from harmful effects of technology.
How Does Your Artificial Intelligence Strategy Address Ethical Concerns?
Ethical concerns and privacy challenges are still two of the biggest concerns hampering the wider adoption of generative AI With VPS server. Businesses must exercise caution and move carefully when implementing artificial intelligence. For this, they need an AI strategy that is specifically made to target those ethical, security and data privacy issues. You need to decide which tasks need to be performed by humans and which ones to be performed by machines based on the law, public policy, best practices and citizen expectations.
Which of these questions are you struggling to find answers for as an IT leader? Share it with us in the comments section below.
