As AI technology continues to advance, enterprise businesses need to learn the top three ways to effectively implement AI as a service.
Artificial intelligence (AI) has increasingly moved to the forefront of societal, economic, and even ethical debates about our future. Although the technology behind AI continues to grow, its potential often overshadows its practical applications for enterprise businesses. This is partially the reason only 14% of firms have deployed AI in production. Here are some practical methods on effectively implementing AI as a service for your business.
Build Foundational Knowledge of AI
Learning about the advancement of AI and its applications seems like a daunting task, however, there are many resources available for learning about AI’s history, and its modern day applications.
AI Knowledge Resources
There are a number of resources available for enterprise business leaders, such as CIOs and CTOs, to learn more about AI. Courses such as those provided by DeepLearning.AI or Coursera can offer business-side information on AI and its practical implementations.
In addition to learning about the history and current landscape of AI, it’s important to understand its different applications. Google AI offers a number of top-level, free guides that cover important AI applications. These include applying AI for social and environment change, as well as designing AI products and implementation in a human-centered way.
Employee Buy-In
Although key team members and leaders in your organization need to have a foundational knowledge of AI, enterprise businesses must ensure that their employees understand the value AI can bring to their jobs as well.
One of the most prominent barriers in enterprise businesses adopting new technologies is garnering employee buy-in. AI is a particularly challenging topic to tackle because of its seemingly uncertain future and its perceived threat to job security. These concerns are valid and can be addressed in a number of ways:
- Education: Being thoroughly educated on the landscape of AI and its future means leaders can better communicate how it will play a role for their company and employees. This education should be at the forefront of the company’s digital culture.
- Company Culture: A fundamental part of gaining employee buy-in is fostering a company culture that is forward thinking and innovative. For startups and tech companies, this might already be the norm. However, legacy companies might have a more difficult time making this transition. An effective way to jumpstart this process is upskilling employees.
- Upskill Employees: Employees do worry about AI replacing their jobs. In reality, AI’s implementation as a service will assist and better employee capabilities, rather than totally replace them. The best way to help employees understand this is to provide them with hands-on experience. Employees deserve to spend time and training with the tools that will become an integral part of their company’s operations.
Equally important as understanding AI and garnering employee buy-in, is building an understanding of the problems your business faces that AI could potentially address. A 2020 IBM survey of over 4,000 US, EU, and Chinese businesses showed that cybersecurity, task automation, and virtual assistance are the top use cases for AI. Let’s look into how AI can be leveraged to tackle these challenges.
Leverage AI for Cybersecurity
One of the fastest growing avenues for AI implementation is cybersecurity. Cybersecurity companies use AI to detect malware and potential attacks. Advanced solutions train themselves and learn from human behavior to prevent breaches from ever happening. Cybersecurity tools built with AI can read more data in a timely manner, allowing for business scalability.
The AI cybersecurity space is only growing. Newer players like Deep Instinct are tapping into the more advanced capabilities of AI and machine learning (ML) to create an autonomous, yet highly powerful solution for enterprise businesses.
Enterprise businesses should especially consider implementing AI cybersecurity as new frontiers such as the metaverse and crypto currencies grow into the mainstream. These new technologies are exciting, but could put businesses lacking proper cybersecurity in a vulnerable position. We suggest enterprise businesses also catch up on the pros and cons of implementing AI cybersecurity to better familiarize themselves with the space.
Also read: Best Network Security Software & Tools of 2021
Automate Tasks
The most practical application of AI as a service is automating repetitive administrative tasks. This implementation of AI allows for businesses to simultaneously scale and cut costs.
One example of this is Robotic process automation (RPA) software. RPA software allows enterprise businesses to deploy bots into third-party applications to automate tasks. RPA software allows for a variety of use cases, including extracting unstructured data, opening and moving files, and completing keystrokes.
Also read: Top RPA Tools 2021
Virtual Assistants
Virtual assistants and chatbots are very effective implementations of AI, especially for enterprise businesses looking to optimize customer support. Because these solutions are automated, wait times are effectively cut and customers are able to get answers immediately.
Although there might be worries about losing the human quality behind customer service, chatbots and AI are continuing to improve listening tools as well as personalized web visits for customers. In fact, the conversational AI realm is growing just as fast as the AI cybersecurity space.
Virtual assistants are build for a number of different industry verticals, including:
- Contact centers
- Insurance
- Financial services
- Healthcare
- E-commerce
Not only can conversational AI platforms assist enterprise businesses with their customer relations, but also with internal employee tasks. Solutions such as Aisera include virtual assistants that act as 24/7 support systems for employees to finish onboarding, or perform more clerical tasks such as signing up for insurance and retirement plans.
The Challenges of AI
As we’ve seen, there are many practical applications that enterprise businesses can adopt to implement AI as a service. Still, there are challenges executives face that could prevent AI implementation in the first place.
According to Deloitte, one of the biggest challenges enterprise businesses might face is integration with existing processes and systems. Luckily, many companies developing AI solutions understand this, and offer both onboarding assistance and native integrations in their services.
Another challenge that was previously mentioned is employee buy-in. As with many other digital transformations, garnering the trust and support of your employees in implementing AI as a service could prove difficult. This is especially true for legacy enterprise businesses. Ultimately, it’s the responsibility of key business leaders to foster a company culture that welcomes these new technologies.
Finally, the last challenge is cost. Many executives feel technologies and expertise are too expensive. Although implementing AI definitely comes with a hefty price tag, enterprise businesses must take into consideration the level of scalability it brings.
By implementing cybersecurity, automating tasks, and adopting virtual assistants, enterprise businesses can ultimately cut costs and focus on scaling their businesses effectively and efficiently.
Read next: The Impact of AI on Unified Communications
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