3 ways to know if you’re ready for AI

Does the proliferation of ever-evolving artificial intelligence (AI) tools have you confused and concerned about missing out? Given the countless providers, it’s a legitimate concern when you’re seeking AI solutions.

However, before evaluating AI tools, you need to determine if your business is ready for AI. Start by asking these three questions:

1. Have you identified potential improvements that will benefit from AI?
Analyzing what specific supply chain process enhancements you’re looking for can reveal more cost-effective and simpler options than using AI technology. However, the more complex your supply chain management goals, the more you’ll require — and benefit from — the power of AI and machine learning (ML).

ML algorithms are a key part of AI solutions. They can analyze massive amounts of data and provide insights traditional data analysis can't. These insights can help you make better decisions about your supply chain, such as finding more cost-effective and reliable suppliers. AI technology can also help you evaluate carriers and establish digital contracts with the most efficient and reliable ones.

2. Are your people prepared for AI?
Adopting AI-powered technology presents you with challenges beyond technology selection. Creating a positive employee mindset can be tough: AI-generated insights may seem strange to your subject-matter experts (SMEs).

For example, a North American manufacturer uses AI to buy coal. ML algorithms identify a link between the cost of North American coal and seasonal rainfall in China's Sichuan province. When rainfall is high, Chinese hydropower is at full capacity, industrial coal consumption drops and the global spot price of coal falls. The opposite happens during droughts. However, basing purchasing decisions on esoteric indicators like rainfall rates on the other side of the world may be difficult for your global sourcing SMEs to accept.

Successful adoption of AI requires management strategies that foster trust. Present AI as an enhancement to — and not a replacement for — subject-matter expertise. AI needs to be viewed as a tool, not an oracle. To gain employee buy-in, identify specific use cases where AI will reduce workloads and streamline complex processes, communicate goals and provide regular progress reports.

3. Is your organization AI-ready?
It’s vitally important to assess the capacity of your IT ecosystem before incorporating AI into your supply chain operation. Evaluate how AI will fit in with the existing infrastructure in the short term and as a potential replacement for your legacy systems in the long term. Create a roadmap to prioritize integrations before moving to the new platforms. Then retire redundant systems and those that are no longer relevant.

A successful AI model also depends on the quality of your training data. SMEs are critical when building precise models due to their comprehensive understanding of supply chain relationships. Make sure your SMEs feel valued for their contributions to AI model development. Proper framing and clear communication will help overcome objections and their resistance to change.

The AI revolution is already in progress

Artificial intelligence-powered technology will fundamentally transform supply chains within the next five to 10 years. AI will usher in a new era of improved efficiency and cost control. To reap these benefits and keep pace with the competition, your supply chain organization needs to take a calculated approach to adopting this technology. Begin with thorough business-readiness assessments and then evaluate and select the most suitable AI-powered solutions for your needs.

Contact us and see how NTT DATA’s Supply Chain Consulting Transportation practice will help you leverage AI technology, revolutionize your supply chain process and realize your organization’s full capabilities. Our top supply chain talent, enabled by proven, leading-edge digital assets — tools, methods and content — delivers actionable insights and measurable outcomes to some of today’s largest and most complex supply chains.