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Is your company's AI strategy falling short?

March 20, 2020

AI Strategy: According to Harvard Business Review, artificial intelligence (AI) is estimated to add $13 trillion to the global economy over the next decade. Companies are rushing to adopt AI and other smart technologies into their businesses. Despite their efforts, most companies are falling short with only 8% widely implementing AI throughout the organization. Many companies are applying AI for small pilot programs that only address one organizational process. The failure to widely administer an AI program is resulting in minimal to no return on investment (ROI). Company leaders who were expecting large ROI’s can become disillusioned with AI and smart technology.

How to Scale: AI-enhanced Technology works best when it is enacted to address broad organizational priorities rather than isolated business issues. For freight brokers, that means strategically adopting AI Technology to tackle the large scale business processes of the organization. Start by identifying the decision-making processes that could be improved and then determine what data is needed to provide insights into how to improve these processes.

To get the most out of AI-enhanced technology identify areas of the company that cut across business functions such as customer service. Freight Brokers have a multitude of customers including internal customers, carrier customers, shipper customers, and driver customers, so improved customer service is an easy starting point. In order for the process to work all customer-facing employees need to be involved in the implementation strategy including Customer Service Managers, Carrier Sales Representatives, Customer Sales and Representatives, and Accounting. This is especially true of end-users who can give feedback and make suggestions on how to refine the process. The business processes being measured should be quantified and tracked over time. Refinements need to be made continually according to the results. Management should align the company’s culture, structure, and work tasks to support broad technology adoption, and ensure all of the company’s employees are making it part of their daily workflow. Companies that are successful at scaling AI-enhanced technology spend ar a large portion of their analytics budget on adoption techniques like workflow redesign, communication, and training. People are resistant to change, so a strategy needs to be developed to compel end-user adherence.

Get Creative: One creative brokerage company gamified its new technology to get employees to adopt it. Employee usage was monitored and those that used it the most were rewarded with prizes and financial incentives. Another company revamped the whole workflow process to coincide with the release of the new technology. This strategy prevented employees from going back to the old system that they were used to.

Going Forward: Companies need to adopt a test and learn mentality and reframe mistakes as a source of information rather than a problem. Most technology applications will not have the desired results on the first iteration. Getting user feedback and incorporating it into the next version will allow for a constant agile cycle of learning and development as the technology moves forward. As employees see their input being adopted they become more involved in the process and begin to see the bigger picture. This encourages employees to collaborate with colleagues across the organization, creating a positive feedback loop. As employees see the benefits of the technology they learn to work with machines to outperform colleagues in other companies.

Cover image: Photo by Franck V. on Unsplash

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