The technology world is moving at lightning speed, and for many managers, it is difficult to keep up. The offerings in artificial intelligence (AI) are especially overwhelming. How do you implement AI effectively in your organization? What are the right steps, and what do you need to watch out for? This article addresses these questions.
While the benefits of AI are pretty clear, the dangers and pitfalls are not always. Therefore, many organizations are still searching and do not have a clear strategy. We spoke with HPE’s CTO, Fidelma Russo, to find out what she thinks is the right approach.
It is a fact that AI is the future, and as an organization, you cannot afford not to invest in it. Russo confirms this and argues that companies that do not embrace AI risk being overtaken by competitors who leverage AI to deliver better products or services.
Also read: CEOs embrace AI, but knowledge gap threatens strategic decisions
Investing in AI is not an option, but a necessity
Investing in AI is not optional. However, it must be done in the right way. According to Russo, IT teams have a more positive attitude toward AI than in previous technology developments. If an organization does not facilitate AI, it will eventually create “shadow AI,” similar to “shadow IT” with the rise of the cloud. This poses significant risks, such as corporate data falling into the wrong hands or being inadvertently added to AI models.
During the rise of the cloud, IT teams often used corporate credit cards to rent infrastructure from cloud providers independently. A similar situation may arise with AI, but not only within IT teams: business teams also want to get up and running with AI quickly. To stay in control, it is vital that IT administrators proactively offer AI workloads to both IT and business teams.
Many AI applications will be developed within business teams with support from IT. This is because business processes rely heavily on specific business knowledge, which can only be deployed effectively if included in the models.
Reliable AI
Another essential aspect is the reliability of AI models. Organizations must ensure that their employees are working with AI systems equipped with the appropriate “guard rails.” This means that AI models can explain their decisions, generate ethical and verifiable outcomes, and do not collect or use unwanted data.
Companies must also consider user rights within datasets. After all, not all data should be accessible to everyone. For example, consider an HR chatbot: if an employee asks about the executive’s salary, it shouldn’t have the answer. The same goes for confidential HR files that could suddenly become insightful. Clear data policies and access controls must prevent these situations.
The importance of data
While caution should be exercised with data, data is also the fuel for AI. Organizations must ensure access to valuable corporate data so AI applications can be used to their full potential. A well-functioning “data fabric” is crucial – a solution that integrates with data on-premises and in the cloud. This makes it possible to link different data sources, including silos within the company, to AI models.
For example, data sets at the “Edge,” such as sensors in manufacturing or maintenance processes, can be valuable. By leveraging this data effectively, organizations can use AI more broadly and achieve optimizations.
Sharing data within departments
An organization has multiple departments, such as sales, customer service, marketing, supply chain, HR, logistics and manufacturing. These departments often work with their own IT systems and databases; the culture is also often that those are their systems. This not only leads to data silos but also invisible data silos. Deploying AI effectively requires a change in culture and mindset: all data must be shared within the organization to perform analyses based on all available information. Of course, access controls should be applied in the case of confidential data.
Investing in people and AI knowledge
One of the biggest obstacles to implementing AI is the lack of AI knowledge. Companies struggle to find staff with the right skills and strategies for AI. Russo emphasizes that investing in talent development and training is crucial so employees can apply AI effectively.
In addition, AI will change the job market. It will create new jobs as well as replace existing ones. We are in a time when many people are retiring and the labor market is facing shortages. AI can help meet these challenges by making work more efficient.
The future of AI
The future of AI within organizations looks promising. According to Russo, AI offers benefits not only for companies, but also for society. For example, AI can contribute to better health care and provide support for the elderly. Therefore, it is important that companies see AI not only as a business investment, but also as an opportunity to make social impact.
Speed of innovation
One tricky challenge is the speed at which AI is evolving. Companies may struggle to keep up with these innovations, which can lead to reluctance to invest. Russo encourages companies to experiment and dare to make mistakes – within a controlled environment, of course. That might include placing AI workloads alongside key data in your data center. A culture of innovation, where teams are encouraged to explore new technologies, is essential to achieving and maintaining competitive advantage.
Conclusion
For managers, navigating the AI landscape is a complex but necessary task. It is crucial to understand the benefits of AI, set up the right infrastructure, and invest in talent and training. In addition, companies must be willing to experiment and collaborate to harness the full potential of AI. By following this strategy, companies can not only remain competitive, but also contribute to a better future for society as a whole.