As a retail consultant, I am excited about how AI can be used to support small—and medium-sized business (SMB) retailers.

We decided to address the problem of receiving too much information today. No one has time to wade through the mountains of reports we are getting, so I decided to test which free AI solution will deliver results for your shop.

We chose free because most SMB retailers are currently experimenting with AI, and as a result, many are utilising free AI solutions. There is no point in testing something few are using.

We extensively evaluated six leading free AI tools to answer this question, testing them against real-world retail reporting scenarios. We made and rated over 200 reports in total. What we discovered might surprise you, but the results certainly did surprise me. This analysis will be helpful and save you a lot of time.

What the test is addressing

There is a significant gap between the data and the time and knowledge needed to use it effectively. A modern POS system like ours generates hundreds of reports, which require considerable time to review to identify sales patterns, inventory levels, supplier performance, and financial statements. However, finding time to extract meaningful insights from these reports is another matter.

Yet the promise is that AI tools can do this and quickly process reports, identify trends, spot anomalies, and suggest actionable improvements.

The Free AI Landscape

Like so much in the world, not all AI tools are equal; some are better than others, and each one has account limitations.

We tested six popular tools to help you navigate these options:

ChatGPT (OpenAI)

Claude (Anthropic)

DeepSeek

Google AI

Grok 3

Qwen

Evaluation Criteria for AI Tool Performance

Now, we know that all of them are good, but there is always a case where even the best six runners in the world have one who is better, and that is what we wanted to find out: the best free AI for retailers.

Each tool was evaluated on its ability to handle our tests based on these criteria:

Information Accuracy

Accuracy formed the cornerstone of our evaluation. Without accurate information, even the most sophisticated analysis becomes worthless for making informed business decisions. We meticulously verified whether each AI tool could process retail data without introducing errors or misinterpreting figures. This involved cross-checking calculations against known values and assessing whether the tools maintained data integrity throughout the analysis. In retail, where margins are often tight, minor inventory valuation or sales forecasting inaccuracies can lead to costly mistakes.

Clarity of Presentation

Accurate information is only valuable if presented in an understandable format. We assessed each tool's ability to structure information logically with clear headings, appropriate visual elements, and a coherent flow that retail managers could easily navigate. We examined whether complex data was transformed into straightforward insights that wouldn't require a data science degree to interpret. A good report should communicate the key points to a retailer without requiring them to wade through jargon.

Actionable Insights

Data without direction offers limited value to retail businesses. We evaluated each tool's ability to convert raw information into practical recommendations that retailers could implement. I am very proud that our POS system provides our customers with tools they can utilise. I want the AI report to do the same. I want to know what specific opportunities were identified in my inventory optimisation, which products are underperforming, and what concrete actions I need to take from my supplier. Good tools should describe what is happening and what should be done next.

Business Relevance

We evaluated each tool's ability to focus on issues that matter most to Australian retailers rather than generic business statistics. Did the AI for example identify seasonal trends in an Australian retail cycles, did it highlight my supplier performance to my business. Information that is not relevant creates noise rather than value.

Consistency in Analysis

Consistency in reporting is crucial for tracking performance over time and making reliable comparisons. We examined whether each AI tool maintained a consistent approach to analysis in its report and whether its outputs provided a coherent narrative. We do not want contradictory findings. Retailers need to trust that the insights they receive follow logical patterns and don't send them in conflicting directions. Inconsistent analysis can lead to confused decision-making and undermine confidence in the technology itself.

This comprehensive evaluation framework enabled us to assess each AI tool beyond its surface capabilities, focusing instead on how effectively it would serve the practical needs of Australian retailers wanting to extract value from their business data.

Test 1: Long Trend Stock Report Analysis

The first test was designed to evaluate how the AI would perform if it were given a vast amount of data that retailers are receiving. If the AI cannot handle the data, it's of minor use to retailers. Retailers have lots of data today.

Now, understanding inventory performance is critical for any retailer. Seasonal trends, slow-moving items, and bestsellers all impact their bottom line, so we ran a comprehensive stock trend report spanning hundreds of pages. It's the kind of data most retailers can obtain but rarely find the time to analyse correctly. Our test data spanned 12 months and exceeded 300 pages in length.

Tool Performance

ChatGPT

Failed almost immediately, as it ran out of credits, rendering it essentially useless for comprehensive stock evaluation. Even before hitting its limits, it failed to provide actionable insights that would aid practical retail decisions. The reality is that a retailer, after running this report, would almost certainly want to rerun it to see whether anything different changes the outcome. I might have tested this year and last year, but here I get nothing. As such, we immediately dropped ChatGPT.

Claude

Initially performed better. It identified some fundamental product trends on the first run. Then it ran into credit limits. However, it did identify some fundamental product trends, but its inability to handle follow-up questions made it impractical for the iterative nature of retailers' needs. As such, we dropped it immediately.

DeepSeek

Attempted a different approach to the credit limit problem. It took only a tiny section (6%) of the information. While this allowed it to complete the task without running out of resources, it did not give much.

Google AI

The first problem was that Google required CSV files, while all the others accepted Excel format, which we preferred. However, it did identify fundamental product trends; however, we all felt it lacked the depth needed for effective inventory management. Its surface-level insights wouldn't provide much of a competitive advantage for retailers looking to optimise stock levels.

Grok 3

Boy, were we impressed with this AI. It took the entire report without issues. It then provided a detailed trend analysis that would help retailers make smarter decisions. For example, it identified some products specifically for BBQs and reported that they sold well during the summer. It also spotted anomalies that would be easy to miss in manual review, such as products that underperform only during specific weather conditions.

Qwen

It performed admirably by identifying anomalies and supplier diversity trends, though it didn't match Grok 3's depth. It correctly helped identify problematic stock items. Unfortunately, it offers fewer actionable recommendations for improvement than Grok 3.

ChatGPT failed

Test 2: Trial Balance Analysis

Accurate financial reporting is the backbone of retail success. The second test focused on a small compact trial balance dataset. What we wanted was an analysis that didn't require an accountant to understand.

Tool Performance

DeepSeek

It produced precise observations but struggled with depth when analysing discrepancies. Its summarised approach meant that nuanced financial issues, which could significantly impact a retail business, were overlooked.

Google AI

Here, we got straightforward summaries that aligned with our general ledger data but it lacked depth in identifying anomalies. We felt that although it was helpful for essential reconciliation, it wouldn't alert a retailer to subtle patterns.

Grok 3

Wow, it delivered a detailed financial summary with cross-referenced data for accuracy. It flagged discrepancies that required further investigation, allowing us to explore these issues. This capability could be invaluable for retailers without accounting expertise in maintaining the financial health of their business.

Qwen

It did a good job of highlighting significant balances and unexpected changes effectively. Again, it did not match Grok 3's level, but it did come up with much good stuff.

Test 3: Supplier Purchases Report

Managing supplier relationships is critical for maintaining healthy margins and consistent product availability. The third test examined a supplier purchases report to evaluate performance, track expenditures, and identify inefficiencies.

Tool Performance

DeepSeek

It did produce some quick overviews. It struggled with detailed metrics, such as cost per transaction or order accuracy. Its summarised approach meant it missed some critical inefficiencies; we did not think it was trivial, as these sorts of things directly impact margins.

Google AI

It did provide a structured summary but lacked in-depth spending analysis by category or supplier benchmarking. While helpful for basic understanding, we did not see key KPIs, such as identifying problematic vendors.

Grok 3

It did offer comprehensive supplier evaluations with detailed metrics. It identified inefficiencies. We thought it was suitable for managing dozens of suppliers. It was good, with its actionable tips.

Qwen

It did highlight anomalies as well as Grok 3 in the supplier but lacked actionable details.

Summary Performance 

When evaluating these tools specifically for retail applications, clear patterns emerged across all three test scenarios:

Practical Implementation for Your Retail Business

Understanding how these tools perform in controlled tests is helpful, but implementing them in your daily operations is where real value emerges. Here's a practical approach to leveraging AI for business improvement.

Start Small and Focused

Begin with a specific business challenge rather than trying to analyse everything at once. Consider identifying your slowest-moving stock items for clearance, evaluating which suppliers offer the best value for similar products, or analysing sales patterns to optimise staffing during peak hours. Starting with a focused approach allows you to see tangible benefits quickly while building your comfort with the technology.

Prepare Your Data

Export relevant reports from your POS system in a format your AI tool can process. Depending on what tool you use, you need CSV or Excel. I prefer Excel but its your call. Check first that your data is clean and good. If you feed the AI rubbish, you will get rubbish back.

Ask Specific Questions

Frame your queries in specific, actionable terms rather than general requests. Instead of asking the AI to "Analyse my stock," try something more targeted, such as "Which product categories show seasonal patterns, and when should I increase inventory for winter?" Similarly, rather than requesting the AI to "Check my finances," ask, "Are there any unusual expense patterns compared to last year, and which categories show the largest percentage increases?" Specific questions yield specific, actionable answers.

We found that general queries often provided incorrect answers, requiring multiple attempts to obtain a satisfactory response.

Implement Findings Systematically

Test your questions systematically and record the question that yields the answers you want. This systematic approach ensures that AI becomes a valuable part of your business improvement cycle rather than just an interesting experiment.

Focus on applying insights

The best analysis is useless if it is not applied. Each of your analysis sessions should end with clear action items to be implemented and tracked.

Recommendations for Australian Retailers

Based on comprehensive testing and practical retail experience, here are my specific recommendations for retailers looking to leverage free AI tools:

Use Grok 3 as your primary analysis tool. I am told it will soon be charged, but now it appears to be the best in the free AI market. We were impressed with its ability to handle complex questions and our interactive questions, which is excellent if, like me, you like following your natural curiosity.

"A good question in business does not lead to an end; a good question opens doors you never knew existed."

Consider using Qwen; it's excellent. We found it helpful as it gave a good second opinion. It can be especially valuable when making significant business decisions.

If you're currently using ChatGPT or Claude, be aware of their significant limitations for business analysis. Their credit restrictions make them impractical for the iterative analysis that delivers real value. You may find yourself frustrated when analysis suddenly stops.

Conclusion: The Future of Retail Intelligence

Retailers, rather than using intuition alone, can use the Free AI tools now available to gain insights.

A Point of Sale (POS) system is used by retailers to manage their shops.

The POS System

Hardware: The Physical Backbone

Every POS system includes hardware components that facilitate transactions. Common examples include:

• Terminals: Countertop units or mobile tablets are used to process sales.
• Barcode Scanners: Quickly identify products and prices.
• Receipt Printers: Generate paper or digital receipts for customers.
• Cash Drawers: Secure storage for cash transactions.
• EFTPOS Machines: Widely used in Australia to process card payments efficiently.

Software: The Brains of the Operation

The software component powers the functionality of a POS system:

Sales Processing

Inventory Control

Tracks stock in real time. This enables retailers to monitor their stock.

Customer Relationship Management (CRM)

Stores customer data to build loyalty programs.

Reporting and Analytics

Provides insights into sales trends and staff performance.

How POS Systems Transform Aussie Retail

Streamlined Operations

POS systems automate many manual tasks, allowing businesses to operate more efficiently:

• Automatically adjust stock levels after each sale.
• Generate detailed reports for financial tracking and decision-making.
• Process payments.

Data-Driven Decision Making

Gets the retailer information that helps them make better decisions:

• Identify top-selling products to optimise inventory.
• Identify dead stock For example, a Melbourne newsagent discovered that 20% of his stock, using this insight from their POS system, was dead and not selling.
• Analyse peak trading hours for better staff scheduling.
• Track customer purchase behaviour to tailor promotions.

Enhanced Customer Experience

Modern POS systems improve the shopping experience by:

• Reducing queue times with faster checkouts.
• Offering personalised recommendations based on purchase history.
• Managing loyalty programs seamlessly.

Real-World Benefits from Our Users

The Future of POS in Australia

As we move forward, POS systems will become even more integral to retail success:

Omnichannel Integration

The shop will need to be connected to the internet

AI-Powered

AI is already investigating many aspects of the shop. We feed information from a POS System into AI to investigate improving shop layouts, inventory, marketing strategies, etc.

Cashless society

It is only a matter of time before Australia becomes a cashless society

Cryptocurrencies

With bank fees the way they are now, it is only a matter of time before we see a growing movement to crypto.

Conclusion: Empowering Australian Retail

A POS system is an investment in your future retail business.

Explore our top POS System, which has been used in thousands of stores Australia-wide for over 40 years.

Written by:

Bernard Zimmermann is the founding director at POS Solutions, a leading point-of-sale system company with 45 years of industry experience. He consults to various organisations, from small businesses to large retailers and government institutions. Bernard is passionate about helping companies optimise their operations through innovative POS technology and enabling seamless customer experiences through effective software solutions.

Update: I wrote this article a few weeks ago and was asked about the other free AI model, GWEN, that was recently released. So, I decided to test this one, too, and add it to the list. It's an excellent AI model. Also, for the sake of completeness, I decided to add Microsoft Copilot. So here is the updated list.

No one has talked about artificial intelligence (AI), and now it seems people are talking about little else. We have been actively involved in AI for several years now.

In retail, AI promises to boost sales and reduce operational costs in the POS system. Like everyone else in business, those leveraging AI will stay competitive in a rapidly evolving market. 

Comparison of AI Models

A good leaderboard of what AI models is available here.

But these are not measured on what our clients now use and the problems they encounter. So, to understand the current landscape of AI needs in retail, we compared several leading widely available AI models:

1) DeepSeek

2) Gemini

3) ChatGPT

4) Claude

5) Meta AI Facebook

6) Grok 2

7) GWEN

8) Microsoft Copilot

We tested these models on real-world scenarios that retailers encounter, such as product descriptions, inventory management, customer service, and sales forecasting. We then combined the answers, amended them by hand and came up with answers that we scored 40. We then compared each AI's answer to this score of 40. All of this took us a lot of work.

Our test results showed that Gemini (Google) was the top performer, scoring 39 out of 40. It also offered a comprehensive package with many additional benefits, making it an attractive choice for businesses seeking a robust AI-powered POS system.

Claude excelled in writing capabilities, scoring 37, which makes it most suitable for tasks requiring explicit and engaging content.

ChatGPT and Grok 2 scored 36, demonstrating their ability to handle various tasks effectively. What we liked about Grok 2's answers is that they contained advanced information on items the other AIs did not have. If, for example, a new game came out and you wanted to see what people thought about it, Grok 2 gave the best response. I cannot wait to see Grok 3, which is overdue now.

DeepSeek scored 35 despite being significantly cheaper. It offers impressive performance at a fraction of the cost of other models, making it ideal for businesses requiring API access.

GWEN scored 34, which is a bit lower than Deepseek's, but like Deepseek, it is free. We weren't that impressed with what the AI model could achieve compared to the other models mentioned; it also lacks an API, which could lead to issues in usage.

Microsoft Copilot scored 32, but like Deepseek, it is free and integrates well into Microsoft products that many of my clients use. Again, we weren't impressed with what the AI model could achieve, but if you use Microsoft products, it fits well into the suite. 

However, Meta AI (Facebook) struggled, scoring only 30, but was still included in the assessment due to its potential in specific use cases. Overall, I would not recommend it as your primary AI.

Recommendations

Gemini is likely the best choice if cost is not a concern due to its superior performance and additional features. Google's support and integration capabilities make it an excellent solution for businesses seeking a comprehensive AI-powered system.

However, DeepSeek presents a compelling option for those prioritising cost-effectiveness. At only 2% of the cost of ChatGPT, it delivers nearly comparable results, making it an attractive choice for businesses requiring API access.

Grok 2 is particularly noteworthy, especially with its upcoming update. Its integration with X (Twitter) offers access to a vast source of real-time data, which can be invaluable for businesses that must stay informed about the latest trends and news.

AI in POS Systems: Promises

English and spelling

Not everyone is good at English with AI lousy spelling, and people with bad grammar can communicate in writing better. It also allows them to communicate better with non-English speakers.

Marketing material

AI can be successfully used to write marketing material. A client wanted to create fancy names for their lotto syndicate, so they used AI to help them.

Real-time Predictive Analytics

AI analyses sales data and market trends to forecast demand, helping businesses optimise and prepare for busy seasons. For example, a retailer can use AI to predict a surge in demand. As trends overseas tend to come first before they hit us, they can tell us where the market is going.

Personalised Marketing

AI could provide tailored recommendations and promotions based on customer purchase history and preferences, fostering loyalty and boosting sales.

Dynamic Pricing Optimisation

We like that it can better set prices in real time based on demand. Companies dealing with marketing events often have goods that sell well in that season, but the demand for the product collapses as soon as it's over. We are hoping AI can help us with this, too.

Implementation Challenges

Implementing AI in POS systems can present challenges. The answers are often not as good as they look. They are often wrong, and it's hard to argue with it because they look so right.

The future

It is unclear where the AI market is going. Will consumers want a low-budget or medium-budget, or are they prepared to pay for an expensive system? One company told me they spend $200/month on ChatGPT, which is $2,400 annually. Will the consumer bear that?

The other issue is whether a business needs a car or a truck in AI. In the context of retail POS systems, AI is not just about speed or luxury; it's about finding a solution that can handle the workload efficiently. Businesses need a reliable truck rather than a sports car to carry a heavy load rather than speed.

I am sure there are privacy issues, too. Some AIs are specially built with that in mind. But this all would involve a deeper discussion of data privacy, security, and compliance (such as GDPR or Australian privacy laws) beyond the scope of this post. 

Some industry research shows that over 70% of retailers plan to adopt AI within the next two years. I would not be surprised if it will be closer to 100% in one year, as AI can enhance competitiveness and drive growth.

FAQ: Frequently asked questions

Q: What is the role of AI in POS systems?

A: AI in POS systems promotes boosting operational efficiency.

Q: Which AI models were compared in our tests?

A: The models tested included DeepSeek, Gemini, ChatGPT, Claude, Meta AI (Facebook), and Grok 2. These were evaluated in real-world scenarios such as product descriptions, inventory management, customer service, and sales forecasting.

Q: What were the results of the AI model comparison?

A: Gemini (Google) scored the highest at 39 out of 40, offering a comprehensive package with additional benefits. Claude excelled in writing capabilities, scoring 37. ChatGPT and Grok 2 scored 36, while DeepSeek scored 35 despite being significantly cheaper. Meta AI (Facebook) scored 30.

Q: Which AI model is recommended for businesses with no budget constraints?

A: Gemini is likely the best choice due to its superior performance and additional features. Google's support and integration capabilities make it an excellent solution for comprehensive AI-powered systems.

Q: What about cost-effective options?

A: DeepSeek is a compelling choice for businesses prioritising cost-effectiveness. It offers impressive performance at a fraction of the cost of other models, making it ideal for those requiring API access.

Q: How does AI improve communication in retail?

A: AI helps individuals with limited English proficiency communicate more effectively in writing. It also facilitates better communication with non-English speakers.

Q: Can AI assist with marketing tasks?

A: AI can be used to write marketing material, such as creating product names or promotions. It can also help generate engaging content.

Q: What are the benefits of AI in predictive analytics and personalised marketing?

A: AI analyses sales data and market trends to predict demand, assisting businesses in preparing for peak seasons. It also offers personalised recommendations and promotions based on customers' purchasing history, enhancing loyalty and driving sales.

Q: What challenges are associated with implementing AI in POS systems?

A: Utilising AI can present challenges, such as ensuring the accuracy of AI-generated responses and integrating AI with existing systems. Additionally, although AI responses may seem correct, they can still contain errors.

Q: What does the future hold for AI in retail?

A: The future of AI in retail appears promising, as over 70% of retailers plan to adopt AI within the next two years.

Q: How does the analogy of a "truck" apply to AI in POS systems?

A: In retail POS systems, AI is not just about speed or luxury; it's about finding a solution that can handle the workload efficiently. Businesses need a reliable "truck" rather than a sports car to carry a heavy load effectively.

Q: Are there privacy concerns with AI in POS systems?

A: Yes, very much so. Some AI systems are claimed to be designed with privacy in mind. It remains an essential consideration for businesses implementing AI solutions.

Q: Is a POS system AI?

A: A POS system itself isn’t AI but can be integrated with AI to enhance its capabilities.

Update: The federal and SA governments have blocked access to DeepSeek over its network and directed public servants to stop using and remove it from devices. More details are available here. There are security concerns over the product. 
 

Artificial Intelligence (AI) is now revolutionising the retail industry. It is already changing how businesses operate and engage with customers. I have witnessed firsthand the increasing impact of AI on our retail sector. This article investigates how we anticipate the latest generation of AI solutions will transform the brick-and-mortar retail in Australia.

The retail landscape is evolving rapidly, with AI leading the charge. From inventory management to customer service, AI promises to provide solutions once deemed impossible. 

The Focus Engine: Our Early AI Solution

Almost three decades ago, we created an AI solution that transformed stock ordering for our users. Using the Focus Engine, this system has been a pillar of our service offering and has stood the test of time. No one has been able to match it in our market space.

Key features of the Focus Engine include:

• Widespread adoption: Thousands of our clients have used this solution, many in their daily operations; it is a testimony to its effectiveness and reliability.
• Cost-effective: We've always offered this powerful tool free of charge, making advanced AI accessible to all our users.
• Tailored for specific needs: The Focus Engine was designed to address particular challenges in stock order and excels in this specific domain.

The most telling indicator of the Focus Engine's success is the feedback we've received from our long-standing users. One particular comment I liked by one of our users when talking about the latest update:

"You can update it however you like. Just make sure that it gives the same figures after the update."

It's hard to beat a dedicated AI specially built for one task. However, it does speak volumes about the trust and reliance our clients place on the consistency and accuracy of our AI solution.

ChatGPT in Retail: Limitations and Challenges

Recently, some of our clients have been using ChatGPT. Unfortunately, in tests, its application in retail has revealed some significant limitations:

• Cost concerns: A significant problem with ChatGPT for many retailers is that it's "not particularly affordable." This poses a significant barrier, particularly for small—to medium-sized businesses operating on tight margins.
• Weaknesses in retail-specific issues: Although versatile, ChatGPT frequently encounters the many nuanced challenges unique to the retail sector in Australia. Most of its information is form overseas. 
• Mathematical limitations: One significant flaw of ChatGPT is its struggle with maths and arithmetic, which are essential for numerous retail operations.
• Pattern recognition methods: ChatGPT's strength resides in pattern recognition rather than actual computations, which can pose a significant drawback for retailers requiring precise calculations.

These limitations highlight why solutions like our Focus Engine, designed specifically for retail requirements, remain valuable even against the backdrop of broader AI advancements.

Enter DeepSeek: A Game-Changer in AI

The AI landscape is undergoing a seismic shift with the arrival of DeepSeek, a Chinese AI model shaking up the status quo. It's making waves in the industry, and here's why:

• Unparalleled speed: DeepSeek operates twice as fast as competitors like ChatGPT, allowing quicker response times and increased productivity.
• Cost-effectiveness: Perhaps most importantly for retailers, DeepSeek costs around a tenth of the price of its competitors, making advanced AI more accessible than ever.
• Comparable power: Despite its lower cost, DeepSeek boasts comparable power to the best commercially available AI models.

Here is a table I constructed to show the difference, in particular checkout the costs.

Why DeepSeek Matters for Retailers

DeepSeek's capabilities are particularly well-suited to the retail sector:

• Mathematical prowess: Unlike some general-purpose AI models such as ChatGPT, DeepSeek excels in mathematical problem-solving, a crucial skill for inventory management, pricing strategies, and financial forecasting.
• Improved efficiency: The combination of speed and accuracy means retailers can make decisions faster and more confidently.
• Cost-effective hardware requirements: DeepSeek is less reliant on expensive Nvidia microchips, allowing it to run on much cheaper equipment. It significantly lowers the barrier to entry for retailers looking to implement AI solutions.

These advantages are already impacting the tech industry. Nvidia, a major player in AI hardware, has lost nearly $1 trillion in market value, indicating a shift in the AI landscape. Moreover, DeepSeek's popularity is soaring, becoming "one of the most downloaded apps in the world".

The Open-Source Advantage

One of DeepSeek's most significant features is that it's the "only powerful AI model in Open-source". This open-source nature brings several benefits:

• Public preference: Users and developers alike prefer open systems. They like to know that the systems they use are open for inspection.
• Wider deployment and development: An open-source model allows for broader deployment and faster development of new applications and improvements as developers can see what it is doing.

Speed and Processing Power

DeepSeek's high processing speed makes it particularly suitable for businesses that require quick, real-time decision-making - a common need in the fast-paced retail environment. No one wants to wait unnecessarily.

Privacy and Security Considerations

While DeepSeek offers many advantages, it's essential to address our privacy concerns:

There are worries about the Chinese government's potential data access. It is also an issue with most AIs, as wherever they are hosted, there is a government with potential data access.

Running DeepSeek locally can mitigate some of these concerns. For those concerned about data privacy, I recommend using DeepSeek "for personal or exploratory use only."

The Bigger Picture: AI Industry Disruption

DeepSeek's emergence is more than just a new product launch; it represents a significant shift in the AI industry:

• It challenges US dominance in AI development.
• It positions China as a strong competitor in the global AI race.
• This competition will drive further innovation and development in AI technologies.

Current Limitations and Strengths

While DeepSeek is powerful, it's essential to understand its current position:

• It is only text-based tasks.
• Its focus on these areas means it can provide better-targeted, efficient solutions for many retail operations.
• Its maths and arithmetic are better, but it does make plenty of mistakes.

Looking Ahead with its Cost-Effective AI retail solutions

The emergence of DeepSeek and similar AI models is set to revolutionise the retail industry. We predict that many more AI models will soon copy its approach, making AI increasingly more cost-efficient and accessible. This democratisation of AI technology levels the playing field, allowing smaller businesses to compete with larger retailers in terms of AI-driven capabilities.

Despite these advancements, there's uncertainty about fully leveraging generative AI capabilities in practical applications. However, the potential benefits for retailers are significant:

Enhanced Customer Experience

AI can dramatically improve customer interactions and satisfaction:

• Provide personalised shopping experiences with 24/7 customer support, handling inquiries and potentially leading to simple transactions.
• Use AI-powered recommendation engines to offer tailored product suggestions, mimicking the personalised service of knowledgeable salespeople.

Improved Inventory Management

AI can revolutionise how retailers manage their stock, particularly in predicting demand fluctuations, automating inventory management, reducing waste, and ensuring popular items remain in stock.

Marketing Optimisation

AI tools can significantly enhance marketing efforts:

• Target ideal customers more effectively, maximising marketing ROI.
• Analyse market trends and competitor pricing to optimise pricing strategies.
• Generate more engaging product descriptions and marketing content.
• Analyse foot traffic patterns in physical stores to improve layout and product placement.

What I particularly like about AI is its ability to scan social media to check out current public thoughts. If you haven't tried it, I suggest you do. You can use this feedback to analyse customer sentiment. I will write another article with a step-by-step approach to show how you can do it now in a few days.

This cost-effective AI implementation means that even small brick-and-mortar retailers in Australia can now access powerful tools. By leveraging these AI capabilities, you can streamline operations, enhance customer experiences, and make data-driven decisions to drive growth and profitability.

The Promise of Cost-Effective AI Implementation

The emergence of DeepSeek and similar AI models is set to revolutionise the retail industry. We predict that "Many more will soon copy its approach", leading to AI becoming increasingly cost-efficient and accessible. This democratisation of AI technology levels the playing field, allowing smaller businesses to compete with larger retailers in terms of AI-driven capabilities.

Despite these advancements, there's uncertainty about fully leveraging generative AI capabilities in practical applications. However, the potential benefits for retailers are significant:

Retail technology trends

The rapid advancements in AI technology will transform the retail landscape.

From our early Focus Engine, which has served thousands of clients for nearly three decades, to the latest advancements in AI, we have seen how these technologies can revolutionise stock ordering. Soon, they will move into customer service, inventory management, marketing strategies, etc. Who knows where they will end up?

One thing is for sure: DeepSeek and what I am sure will be similar AI models will represent a paradigm shift in the AI industry.

Its speed, cost-effectiveness, and open-source nature challenge the status quo.

By staying informed about these developments and thoughtfully integrating AI solutions, Australian retailers can boost their competitiveness, enhance customer experiences, and drive business growth.

It is estimated that in five years, AI will drive 55% of Australian consumer spending by 2030. This projection shows how AI will revolutionise retail in our country. As a retail and point-of-sale (POS) systems expert, it is essential to explore this transformation together and its implications for small brick-and-mortar Australian retailers.

So, we will create a new section in this blog, "AI Musings," to explore artificial intelligence's musing on modern retailing. This space will blend AI-generated insights (approximately 80%) with my thoughts (20%) to delve into the most significant technological revolution in retail today.

The State of Modern Retail in Australia

AI dominates discussions at every retail conference today, signalling its emergence as the new frontier in retail technology.

Adopting AI in retail is not just a prospect; it's happening now. Many retailers already implement AI solutions to enhance customer experiences, optimise inventory management, and streamline operations. For example, our clients have been using AI for years in stock control, but no one is talking about it, and we need to.

I heard about chatbots handling customer queries in a retail firm a few days ago. It was expensive, but as AI becomes more accessible and affordable for businesses of all sizes, we will soon see it in almost all stores.

How AI is Transforming Australian Retail

Personalised Customer Experiences

AI will revolutionise how retailers understand and cater to individual customer preferences, offering a more personalised shopping experience. And it will not take long. If such a system is live in 10,000 shops in one month, that AI will have 800+ years of experience at the end of the month.

Smart Inventory Management

AI is already in our POS system and crucial in predicting demand and optimising stock levels, helping retailers reduce waste and improve efficiency. It has proven vital for retailers who often struggle with inventory management. AI-powered systems can analyse every stock item in the shop with its historical sales data, seasonal trends, and even external factors, like weather.

AI-Powered Customer Service

Chatbots and virtual assistants are improving customer support across online platforms. Currently, 47% of consumers feel comfortable using AI for product selection, while 75% remain cautious about AI handling high-value purchases.

Enhancing In-Store Experiences

AI is set to transform the in-store experience. Retailers use emotional recognition tools to detect customer frustration and seamlessly transfer to human support. This blend of AI and human interaction could be a game-changer for small retailers looking to provide personalised service while optimising staff resources.

Practical Considerations

Cost vs ROI for Retailers

Implementing AI solutions today requires a significant investment, but this is rapidly changing. DeepSeek-R1 is roughly comparable to ChatGPT GPT-4 Turbo, and it is $2.19/128k token, while ChatGPT is $30/128k token, a cost savings of about 93%.

Future Trends in Australian Retail with AI

Looking ahead, the future of AI in retail is bright. By 2030, AI is expected to create 200,000 jobs and $115 billion in economic value, which presents enormous opportunities for retailers of all sizes. That is almost 10% of the Australian economy now.

Voice Commerce

The growth of smart speakers and voice-activated shopping is expected to continue, offering new ways for customers to interact with retailers. I know some clients who now use them in the shop as a translator, and I do, too here. It has helped.

Conclusion

AI is undeniably reshaping the landscape of Australian retail. It is now transforming shopping experiences, retail operations, and customer engagement strategies. We intend to explore this topic here. I encourage our readers to share their thoughts on how they see AI shaping their shopping experiences or what trends they're most excited about.

Let's see how it goes forward together.

I hope you enjoy the new section, "AI Musings."

As a programmer specialising in retail and Point of Sale (POS) systems, I recently embarked on an intriguing experiment: using ChatGPT to create a dashboard without relying on my programming skills. Much discussion has been about ChatGPT enabling non-programmers to write code, with dashboards often highlighted as a key example. I decided to test this claim, and the findings were illuminating.

What's a Dashboard, Anyway?

A dashboard is a visual display that displays important information, commonly called Key Performance Indicators (KPIs). These provide a quick visual overview of the current situation, helping us make informed decisions without the need to sift through large amounts of raw data.

For retailers, dashboards transform massive sales data into actionable insights in seconds.

The Experiment: Following a Non-Programmer's Guide

To simulate the experience of a non-programmer, I followed a YouTube tutorial that promised to teach dashboard creation using ChatGPT.

So, I selected this YouTube here. Please feel free to consider this article as my response article to it.

So, I started with data from our POS software's Sales Report, which has comprehensive insights.

The ChatGPT Experience: Not Quite as Advertised

Data Wrangling Woes

My first hurdle was getting the data into the correct format. While our POS system can export to JSON, I followed the tutorial's suggestion. Later, I found that I had made the correct decision as I would dive into Excel many times to manipulate the data. It became a recurring theme throughout the process.

Paid Account Required

Contrary to the tutorial's claims, I quickly discovered that a free ChatGPT account wouldn't cut it. The credits ran out faster than a sausage sizzle on a Saturday morning. The experiment would have ended if I had not had access to a paid account. Let me know if anyone wants a paid account, and I offer reasonable offers. So, I switched to the paid account to continue this experiment.

Dashboard Dilemmas

After multiple attempts, I managed to create a basic dashboard. However, getting it to look presentable was another story entirely. As any retailer trying to spruce up their shop window knows, making things look good is most of the work.

Real-World Retail Challenges

Then, I ran into the problem of using real-world retail data in an experiment. In business, things are not cut and dry. I would encounter these problems here.

Consignment Stock

Items on consignment threw off profit calculations, as they had no listed cost.

Gift Cards

These presented a similar challenge to consignment stock.

Payouts

While these transactions affect sales numbers, they don't contribute to profit.

I only discovered these issues through this exercise, and it took time to learn these problems each time. The solution was to return to Excel, adjust the data, and recreate the JSON file. It was like constantly restocking shelves but with numbers instead of products and then recreating the dashboard.

The Programming Plot Twist

By now, I had spent many hours. So, when trying to calculate the total profit, I hit another wall. After many attempts, I had enough, so I resolved this by going outside the tutorial's framework. I had to break character and lean on my programming expertise. I delved into the HTML code generated by ChatGPT to understand what was happening behind the scenes. Only then did I finally wrangle the dashboard into something usable!

Now I had this, I could select a department, and it would give me these figures and charts.

Now I had something, but were the figures correct? After five hours of this exercise, I did not check, so it was unusable. In programming and business, it's rarely worth it for one-off jobs. You need stuff that, once done, repeats. Here, you must massage the data extensively before using it. The Bottom Line

It was presented as a quick and easy project for someone with moderate computer skills but turned into a time-consuming ordeal that required the following:

• Over five (5) hours of work
• Extensive Excel manipulation
• The ability to read and understand HTML code
• A paid ChatGPT account

Even after all that, I hadn't yet verified the accuracy of the figures—a crucial step that would likely take many hours more if they were wrong.

Lessons 

While quickly creating custom dashboards is appealing, the reality is not yet here.

ChatGPT for Businesses 

Most of our clients are very progressive regarding technology and are as excited about ChatGPT as we are.  

What is ChatGPT

Its an AI chatbot. If you have yet tried out ChatGPT, click here. Make yourself an account, and then give it a try. Ask it some questions, ask it to translate some text into your language, give it some history questions, religious or theological questions, cooking questions, etc. You will be amazed at what it can do. 

This is why businesses today are paying attention to ChatGPT. It is an appealing option for businesses of all sizes looking at improving efficiency because it can save time and money. Exactly what it can do is still being determined.  

Fun fact

I asked ChatGPT to describe itself and put its description into a drawing program; this is how ChatGPT sees itself.

Competitors to ChatGPT

There are several rivals for these products. The most well-known is Bard by Google, but many others are into it; Vicuna is a Japanese product. 

Quality 

Quality is the most crucial point. If the product cannot do the job, what difference does anything else make? Here is a very rough test of the quality of several product results.

I wonder if most users will notice that much difference in quality. All have their strengths and weakness. 

You can check out the quality here and make up your mind.

I feel that the free version of ChatGPT is about as good as Vicuna. Overall I prefer Vicuna for business.

Price

The older ChatGPT is free, but the newer product is $20 per month. The others are all free for now. If you want to try the newer ChatGPT before paying for it, try the others first and the older version of ChatGPT so you will know what you need before jumping into it. One needs to learn to walk before one starts to run.

Availability

All except Bard are available now to an Australian. Bard is officially yet to be open to Australians. If you want to run Bard now in Australia, you need a VPN. 

Everyone is now waiting to see the Chinese product, but it has yet to be available in Australia.

Information

This is a big problem in business; Bard is the only one now with up-to-date information, and the rest are about two years old. Yet a businessperson needs current information. A person will come to a shop and generally wants to know about something recent. This puts significant limitations on its business use in Australia.

Outages

Even with paid services, users need help with using the product. It can be very frustrating. Also, many reports say that OpenAI has made ChatGPT stupider to get faster speeds. 

Accuracy

With a Google search, you know where the information comes from; this is not the case with these products often, and YES, the information they supply is often wrong. 

Since these often do not supply references, you must check the answers you get from these products. Be careful.

Political filter

Except for LLaMA, they all have political filters in place. These can drive you crazy as innocent questions can be refused to be answered as such. Heavy users of these products often will debate if Big Brother is watching them. 

Conclusion

Today we are all paying attention to this technology. It is an exciting technology that has the potential to cut costs and increase productivity. I am more than happy to discuss it if anyone wants. 

Executive summary

> These AI can answer a wide range of questions.
> Businesses are looking for them because of their potential to cut costs, save time, and increase efficiency.
> They all have their pluses and minuses. 
> You may not notice a significant difference in quality 
> These products' limited business applications may be due to outdated information.
> These products give incorrect answers, so you must check their accuracy.