In business, some trends are so widespread that you have no choice but to embrace them. Over the past three years, generative AI has become a trend—it’s in every tech product and every company’s workflow.
It’s a topic that every executive needs to have an opinion on and every company needs to have an action plan for. However, as transformative as AI is, it has just as much potential to wreak havoc as it does to drive innovation. A few wrong steps can cost you a lot of time and money, so it’s imperative to know the best strategies for staying ahead in the AI era.
How To Stay Ahead in the AI Era
Here are some actionable steps to prepare yourself and your business for the AI era.
1. Stay Up to Date With AI Advancements
The first step is to keep up with the artificial intelligence industry. This isn’t as straightforward as it sounds, however, because there is a shocking amount of misinformation around this area of discussion. A recent study by the AAAI (Association for the Advancement of Artificial Intelligence) involving hundreds of AI researchers showed that 79% of respondents believe the “current perception of AI capabilities does not match the reality of AI research and development”.
In other words, the general public lacks a clear understanding of the limitations and capabilities of AI. It’s also wise to be cautious of public figures in the AI industry, such as the CEOs of major tech companies, who are driving this movement forward. As technical as some of their backgrounds may be, their current role is to act as salespeople for AI, and their perspectives are heavily biased due to this fact.
As an executive, you must become a well-informed figure on this topic, with knowledge rooted in scientific fact rather than social perception and “AI hype.” This is essential not only for making the right decisions but also for building trust with your colleagues and employees. Within your data science and engineering teams, there will be people with a technical understanding of these topics, and if your angle on AI doesn’t align with the facts, it could affect your reputation.
Depending on your existing knowledge and your technical proficiency, you can take courses on the basics of AI, follow data science publications, and build relationships with AI experts within your company. Identify the individuals who possess expertise in their field and ensure they are included in your decision-making process.
2. Get Familiar With Different Types of AI Tools
Because current generative AI tools focus on improving efficiency and reducing the time spent on repetitive tasks, you’ll find that they can be used for a wide range of purposes. A lot of the business software you already use will have new AI-powered features, and new tools are built to integrate right into your current workflows. To pick the right tools, you need to know your options.
Here are the prime areas for AI integration:
- Customer service: AI chatbots and AI-powered workflows that empower employees to resolve more tickets in less time.
- HR and admin automation: AI-powered software and workflows that reduce time spent on repetitive tasks.
- Data analysis: AI-assisted data analysis tools can speed up tasks for your analysts and empower non-technical employees to conduct simple data analysis.
- Content creation: Platforms with AI-enhanced tools for creating graphics, generating topics, optimizing headlines, and more.
- Marketing: AI tools can fuel ultra-personalized marketing campaigns to engage customers.
- Programming: Coding assistants can help reduce the amount of time spent on simple tasks and support junior developers.
- Design: AI-powered mock-up tools and prototyping tools can help your designers iterate much more quickly during the early stages of the design and development process.
3. Learn From Other Companies
Because AI is such a huge trend right now, people are diligently keeping track of who is using it and what their results are. There are numerous studies detailing the most successful AI strategies and how to implement them, so always check the data when you plan your own AI initiatives.
You can also follow high-profile cases in real time, as there are companies out there taking big bets on AI right now. One ongoing example is the buy-now-pay-later company Klarna, whose CEO froze hiring and implemented an AI system to do the work of 700 full-time agents. The company has since faced losses and had to begin hiring again, so it clearly went a little too far, a little too fast.
Shopify is another example, with CEO Tobias Lütke making AI proficiency a must-have skill for his employees and implementing a new rule that new headcount will only be granted once it has been proven that AI can’t do the job instead. The success or failure of cases like these can help you shape your own innovative strategies, or you can play it safe and follow in the steps of the most successful companies.
4. Understand Both the Capabilities and the Limitations of AI
The effectiveness of any AI tool is highly dependent on the context it’s used in. With AI coding assistants, for example, you’re likely to see much better results when you give the tool to a team of experienced senior engineers compared to a team of juniors.
The reasons are simple: Generative AI works best when the prompts you give it are highly specific, accurate, and relevant. If you can ask for the right things in the right way, it can help you get the job done more quickly. If your knowledge is lacking, however, you’ll end up relying on the AI to suggest the right things to do, and this is where the quality of the output can decline rapidly.
In this sense, AI tools are exactly the same as any other tool. The more experienced and knowledgeable the wielders are, the better the results. If you don’t keep this in mind, you can end up putting too much emphasis on the tools and not enough on the employees who use them.
For automation tools in the HR or marketing sector, just about any team should be able to improve efficiency and output. The key is to go in with an open mind and flexible expectations, so you can find a good balance between saving time, increasing output, and maintaining quality.
5. Treat Every New AI Strategy as a Trial Run
The ultimate tip when it comes to AI strategies is to be flexible. Treat every new tool and workflow as a trial run, and be prepared to discontinue them if you don’t see the desired results.
This means you need to avoid making extreme or irreversible decisions, such as laying off large numbers of employees, dismantling your existing processes, or completely overhauling your tech stack.
You also need scalability, meaning the ability to dial up power when needed and turn it down again if necessary. To achieve this, leaders are adopting cutting-edge GPU cloud rental services, enabling them to access dedicated compute on demand. You only pay for what you use, when you use it, allowing you to experiment with new AI strategies without worrying about costly and time-consuming infrastructure investments.
This kind of flexibility is a hard necessity in the current environment, because AI is new and evolving; it’s easy for mistakes to happen and plans to fall apart. Ensuring you can easily pivot away from ideas that aren’t working out is essential for long-term success.
Checklist: Everything You Need To Stay Ahead
- Learn the basics: If you don’t know anything about AI, change this immediately.
- Source information from the right places: Take steps to avoid AI hype and learn from actual engineers and industry figures.
- Surround yourself with experts: Identify the individuals within your company who possess in-depth knowledge of AI, and if you don’t have such a person, consider hiring someone new.
- Learn about the available tools: As a decision-maker, you need to know which tools will work best for your company, which means understanding the options.
- Keep track of what other companies are doing: As more companies place their bets on AI, you need to watch out for what works well and what doesn’t.
- Create reasonable expectations for your AI initiatives: Don’t tell your employees and the world that your new AI-powered tech stack will double profits while using half the resources. Research and test your solutions to gain accurate and managed expectations of what they’ll achieve, and be ready to adjust to changes as you roll them out.
- Always try out new ideas, and always be ready to shut them down: With the right tools and services, you will have the power to try out any new AI initiative you want. Just be prepared to pivot again if you don’t achieve satisfactory results.
Conclusion
Succeeding in AI leadership is all about practicality, flexibility, and scalability. Stay focused on the results, pivot if you’re not seeing the desired gains, and utilize scalable cloud rentals to ensure you’re only paying for the compute you need when you need it.
By staying focused on these three metrics, you can both stay ahead and avoid the common pitfalls of AI, all while being ready to upgrade when the inevitable next big development comes along.
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