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Artificial intelligence has permeated our culture and is revolutionizing our daily lives. Alexa turns off our lights before bed, chatbots manage our online purchases, and Uber tells us when we will arrive at our destination. AI technology is so ingrained in our day-to-day lives that over 68 percent of us use it without even knowing — and trust it without question.
Now, with Amazon’s Alexa for Business and other AI initiatives gaining traction, this technology is entering the enterprise at scale. But how will this level of ease and reliance transfer to the office setting? Will business leaders be able — and willing — to adapt?
Al already transforms business models and opens doors for unprecedented enterprise innovation. By automating monotonous tasks, AI enables employees to focus efforts on critical thinking and higher-level tasks. We’re already seeing this happen with voice-driven software navigation, which automates tasks with simple commands and removes the need for deep, multi-level UIs to complete jobs or find answers. This has a massive impact on business processes and can drastically decrease time requirements for activities such as employee onboarding and administrative inputs.
These benefits have business executives taking a long, hard look at how AI can positively affect companies, but serious reservations remain. The core issue, and the most difficult to overcome, is learning to trust AI.
The key to using AI responsibly and effectively lies in adopting early and applying the technology to aspects of the business that will see the greatest impact, while also building the greatest confidence. Companies can ensure a seamless, effective, and trusted AI transition across their organization by keeping these enterprise AI guidelines in mind.
1. Tailor to your specific industry
There is no one-size-fits-all approach to AI. Instead, companies should build AI skills in accordance with specific industry trends and unique customer needs. Look critically at your existing business processes and tasks to determine which areas of the company would benefit most from AI automation. Seasoned workers may write off a new tool if it does not bring immediate value to an existing system or the company’s unique objectives. This process will ensure the meaningful use, immediate understanding, and earned trust of AI tools upon implementation.
Beyond your company, look at your customers’ top needs to determine which processes and services should implement AI. Retail customers shopping for groceries have vastly different needs than a patient at a hospital or a manufacturer transporting goods. It is imperative to automate aspects of the business that have a positive impact on the customer experience and build further trust between the customer and the company.
2. Design to build user trust
Intuitive design and a fluid user experience are essential to the success of AI adoption. Unless smart, practical design is a foundational part of the process. AI technology risks are inaccessible and intimidating to non-AI experts.
Aside from ease of use, companies must design AI to put fears and skepticism to rest. People trust what they can understand. Users should be able to ask the AI system to show its process by explaining how its response was formed. This proof of accuracy can clarify the analytics or navigate to where information is housed. By eliminating confusing interfaces and providing proof when necessary, well-designed AI systems earn user trust.
3. Aim to eliminate biases
Each individual and team at a company holds a unique perception of situations, processing information subjectively based on their own understanding. AI’s deep-learning removes the subconscious prejudices that humans have, increasing accuracy and reducing company biases. Augmenting results enables the unification of information across teams and facilities, resulting in efficient collaboration.
While business leaders may shy away from trusting AI, the fact is AI is more reliable than employee-generated and communicated information. Seeking out ways for AI to eliminate human errors and discrepancies will improve business results and build trust.
AI is here — and 2018 is the year it will enter the enterprise at scale. While AI can cause apprehension for traditional business leaders, companies can achieve strong trust if executives choose to tailor its application to specific industry needs, design its capabilities with the user in mind, and use it to eliminate human bias. By keeping the core business intact, optimizing the most valuable services, and putting process augmentation in the hands of AI, companies have a lot to gain in adopting this exciting technology.
Rick Rider is product director of technology at Infor, an enterprise software company.
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