Over the past few years, advances made in the field of AI and ML have increased their adoption across industries. The logistics and supply chain industries are no exception, with trade AI gaining in popularity amongst importers, exporters, and customs brokers.
Awareness of the potential benefits of AI – and consequently the demand for AI-powered products – has grown significantly. As a result, AI has become more of a marketing tool, with almost every tech product that automates a process or part thereof being marketed as AI-powered. Current practices in tech evaluation often fail to distinguish between true intelligence and simple automation.
In this sense, AI-powered has become a cliché, somewhat akin to the manner in which the term cloud-based became overused and underdefined about a decade back.
Automation vs Intelligence: Why Automated Doesn’t Always Mean Smart
It’s easy to conflate automation with intelligence, but in the world of trade AI, the difference is crucial. Automated systems excel at processing a massive amount of data quickly, but speed alone doesn’t guarantee valuable insights or informed decisions. True intelligence goes beyond routine automation by leveraging real-time data and data-driven decisions to deliver continuous improvement and a genuine competitive advantage.
This has caused a blurring of lines between what constitutes trade AI and products that merely digitise or automate certain tasks. It makes technological due diligence during the vendor evaluation stage crucial. Besides technical assessments, soft due diligence is also important, as it assesses the provider’s culture, management, and integration capabilities.
The key is to grasp the concept of automation vs intelligence.
While automation involves performing tasks efficiently and rapidly using technology, it can perform only within its defined scope and doesn’t learn or improve.
The implication is that it is more of a tool designed to perform a static task and reduce human effort for that particular task, examples of which could be using macros in Excel to automate data processing. Though automation might have saved human effort, its benefits stop at this point, and is not dynamic or adaptable.
Intelligence – as used in the term AI – refers to the system having the capability of simulating human learning, comprehension, problem solving, and expanding its scope of tasks handled, through an iterative process where the more data it processes, the better it becomes. In this context, trade AI presupposes the ability to adapt, predict, and refine its processing abilities.
Due Diligence Process Checklist to Identify Trade AI Capabilities
Recognising this difference between automation vs intelligence can help users ask the right questions during the vendor evaluation process, thus making their due diligence robust and more effective.
This is all the more relevant while procuring Trade AI solutions, to ensure that the solution addresses broader issues and integrates across all functions, rather than operating in silo’s.
Before initiating the vendor evaluation process, users must have in place a structured due diligence process that can gauge the difference between automation vs intelligence, understand what their business requirements and organizational needs actually are, and then select an appropriate trade AI product.
To do this, a comprehensive checklist for vetting AI claims and ascertaining value-add functionalities is of the utmost importance. Using a cleverly designed checklist can help sift the wheat from the chaff by asking the right questions to separate real capabilities from mere buzzwords and jargon.
A handy due diligence checklist for use during the due diligence process is shared below:
1. Clarify Business Objectives
- Map your organizational objectives and user-specific requirements.
- Ensure alignment between business needs and the capabilities of the trade AI solution.
- Define success criteria to guide the evaluation process.
2. Get a Comprehensive View of Solutions
- Evaluate various trade AI products side by side to obtain a comprehensive view of each provider’s offering.
- Identify whether the solution addresses isolated tasks or enhances end-to-end supply chain efficiency.
3. Assess Intelligence vs Automation
- Does the system simulate learning and problem-solving – or simply automate static tasks?
- Can it adapt to exceptions, process unstructured information, and improve over time?
4. Functional & Predictive Capabilities
- Look for Intelligent Document Processing (IDP), real-time analytics, and predictive features.
- Is the AI system explainable? Can users understand why a decision was made?
5. System Integration & Scalability
- Check for seamless integration with existing systems and smooth data flow across departments.
- Ensure the solution is scalable across business units and geographies.
6. Supplier Evaluation & Vendor Reliability
- Conduct a thorough supplier evaluation to assess the vendor’s delivery record, compliance posture, and risk profile.
- Review key financial metrics and past performance to evaluate long-term reliability and growth potential.
- Request case studies or success stories relevant to your industry.
7. Engage Stakeholders Early
- Engage stakeholders across departments – especially the procurement team – to gather diverse perspectives and ensure alignment.
- Involve both technical and business users to assess usability and fit.
8. Legal & Compliance Review
- Confirm that all material information and facts are disclosed during the evaluation process.
- If needed, engage a law firm to perform legal due diligence and validate regulatory compliance.
These questions are designed to ensure comprehensive vendor evaluation and assist in selecting a trade AI tool that is suitable for the business, considering its scale and complexity, and to support effective decision making.
KlearNow’s Helps You Control Trade Risks
Data is the lifeblood of international trade, and smooth information flows accelerate cargo flows. It is vital to ensure that data is shared on time with all relevant stakeholders, and there is visibility at all stages of the supply chain.
It is therefore necessary that trade AI products need to be designed with a transparency-first approach.
With its customer-centric mindset, KlearNow has always prioritised transparency while designing its trade AI products.
KlearNow’s logtech solutions are designed to automate the end-to-end supply chain and trade compliance process, digitizing documentation and simplifying customs submissions, besides being scalable, easy to integrate, and infusing intelligence in your operations.
Click here to schedule a free demo on how KlearNow can ensure you remain in control.
Frequently Asked Questions (FAQs)
1. What does a thorough vendor evaluation process involve when selecting a trade AI provider?
Diligence involves examining not just product features, but also the provider’s ability to meet your evaluation criteria, including performance standards, quality standards, and cost control. A well-structured vendor evaluation form can help compare offerings objectively and flag potential risks early on.
2. Why should regular reviews of trade AI solutions be part of our strategy?
Trade environments evolve constantly. Regular evaluations ensure that your AI provider keeps up with shifting market trends, complies with updated quality standards, and continues to align with your strategic goals. These reviews also help identify performance gaps and ensure consistent vendor performance.
3. How does trade AI impact cost control and shareholder value?
Smartly implemented trade AI can enhance cost control by reducing manual effort, minimizing compliance errors, and streamlining documentation. By boosting operational efficiency and resilience, it directly supports long-term shareholder value creation.
4. What role does market data play in evaluating trade AI tools?
Market data helps benchmark your vendor’s performance against industry norms and identify leaders who are innovating with AI. Evaluating providers in the context of current market trends can reveal who is genuinely driving progress versus those using “AI-powered” as a buzzword.
5. What legal or IP-related aspects should be considered during vendor selection?
Ensure that the provider retains control over its intellectual property and that usage rights are clearly defined. This reduces potential risks of IP disputes or vendor lock-in. A legal review – often done in collaboration with a law firm – can also ensure the solution complies with regulatory frameworks and protects your business.
