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Overcoming Roadblocks Retailers Face When Implementing AI



Overcoming Roadblocks Retailers Face When Implementing AI

It might feel as though artificial intelligence has reached a critical mass, but it hasn’t. In fact, it’s only starting to make an impact in some sectors, including retail. But, according to findings collected by KPMG, retail AI has room to grow — and a lot of it. And by 2027, AI in retail will balloon to $19.9 billion from around $7.3 billion in predicted spending in 2022, per Meticulous Research.

All this, and only half of the retail professionals believe they’ve scratched the surface of what’s possible when the technology meets in-person shopping. So why the lag time despite AI’s potential? Blame it on the confusion around AI in general.

What AI Is — and Isn’t

Many people don’t understand AI conceptually. This leaves them less likely to invest in the emerging technology, even as they see it working for e-commerce. Or, they feel like AI is limited to robots that stock shelves.

AI is more straightforward than what many retailers imagine, though.

In essence, AI algorithms are mere “if-then” statements. As long as outcome parameters are set, the programming collects, evaluates, and uses data appropriately. And if-then situations happen all the time in retail.

An Example of “if-then” in retail

Say a grocery store manager stands at the checkout lines. When more than three customers are backlogged, the manager opens a new register to make customers happier.

In other words, there are hundreds, if not more, issues that arise on the retail scene that have to be addressed by managers to keep the customers happy and the process running smoothly.

With AI, you could eliminate the need for the manager to stand around keeping things moving. Instead, store cameras or sensors could do the job instead. That way, the managers can take care of other business during business hours and beyond. At the same time, the data collected by the cameras could go through more if-then statements.

If the store is busy every day at 3:00 p.m. and customers are angrily waiting in line, then we need more cashiers at 3:00 p.m. each day.

Making Data-Driven Decisions

Let’s take the situation a step further. The AI sensor could store incoming data and measure the average wait time for customers. Those averages could then help the manager know when employees were most needed to care for overloaded checkout lines. When do the most clean-up situations occur?

There’s practically no limit to the doors that AI software can open.

In Australia, AI fashion booths are gauging customers’ body language and moods to make clothing suggestions. At Starbucks, AI is being used to track bestselling brews and personalize special offers. Which special offers do customers request and receive the most?

Other retail firms are improving their stockroom management, tasking machines with “heavy-lifting” in warehouses. Some stores do a deep-dive by seeing whether customers spend more when they turn right or left upon entering the store. If you know which isle your customers spend the most time on, you can plan better for the spend on displays on those isles as well as promotional coupons.

Gearing up for AI in Retail — Roadblocks Retailers Face

One thing’s for sure: AI can be a powerful retail tool. However, it’s not without roadblocks. Fortunately, most obstacles to adopting AI technologies can be overcome by asking (and answering) a few questions.

1. Why do we want to use AI?

This might sound like a trick question. It’s not. It’s an ethical one. Retailers need to be clear on why they want from AI, and their responses need to make sense. Case in point: If they’re using AI to improve the customer retail experience, — great. On the other hand, if they’re driving sales through AI-powered fearmongering, that’s inappropriate.

Everyone needs to have a bedrock of morality regarding AI’s use. Its potential for good is so vast. But when it’s used for the wrong reasons, it can do great harm. Therefore, the correct reply to this question needs to be centered on service and safety.

2. Which of our processes could benefit from AI?

You can’t explore all the possibilities of AI if you don’t understand where your bottlenecks are. Consider when I was 15 and worked at a fast-food place. I changed the marquee sign regularly. How did I know what to write? Someone at corporate would fax a companywide memo to my franchise owner. Then, my manager would review the fax and give it to me. Not precisely a streamlined system, right?

With AI, one person can schedule a digital sign to go live or even program the sign to change based on anything from the time of day to weather conditions — to on-the-spot sales.

When you’re considering implementing AI in your retail store, start by thinking about what your algorithms would look like in analog fashion — get help if you need to — don’t miss this opportunity. For example, where do you collect and disseminate information routinely? Those are probably areas that could be sped up if you handed them over to AI.

3. Who should help us implement our AI solutions?

When considering this question, did you automatically think, “an AI expert or IT person?” That’s what most retailers assume, but it’s not true. The best person to bring in to help you with your AI applications is an operational efficiency expert. This type of professional will strive to understand your business processes and store, in order to design a satisfactory AI solution for your if-then statements.

You’ll know you’ve found the right partner when you’re getting hit with all sorts of additional questions.

These questions will likely include inquiries about what kind of information you currently collect, which digital processes you might be able to automate, and how you intend to use AI-gathered data to make improvements to your retail systems that are already in place.

Looking Forward

It’s hard to tell how far AI in retail will go. Nevertheless, it’s clear that it’s bound to change the way consumers shop and how stores go about their everyday business. So even if you’ve delayed embracing AI retail solutions, now is the time to let go of your hesitancy and jump on the bandwagon.

Image Creditt: markus spiske; unsplash; thank you!

Scott T. Reese

Chief Technology Officer at Harbor Retail

Scott T. Reese is chief technology officer at Harbor Retail, a design + build firm where he helps bring Harmonic Retail™ to life with intuitive Self-Healing Technology™ and other future-forward digital integrations.


Fintech Kennek raises $12.5M seed round to digitize lending



Google eyed for $2 billion Anthropic deal after major Amazon play

London-based fintech startup Kennek has raised $12.5 million in seed funding to expand its lending operating system.

According to an Oct. 10 report, the round was led by HV Capital and included participation from Dutch Founders Fund, AlbionVC, FFVC, Plug & Play Ventures, and Syndicate One. Kennek offers software-as-a-service tools to help non-bank lenders streamline their operations using open banking, open finance, and payments.

The platform aims to automate time-consuming manual tasks and consolidate fragmented data to simplify lending. Xavier De Pauw, founder of Kennek said:

“Until kennek, lenders had to devote countless hours to menial operational tasks and deal with jumbled and hard-coded data – which makes every other part of lending a headache. As former lenders ourselves, we lived and breathed these frustrations, and built kennek to make them a thing of the past.”

The company said the latest funding round was oversubscribed and closed quickly despite the challenging fundraising environment. The new capital will be used to expand Kennek’s engineering team and strengthen its market position in the UK while exploring expansion into other European markets. Barbod Namini, Partner at lead investor HV Capital, commented on the investment:

“Kennek has developed an ambitious and genuinely unique proposition which we think can be the foundation of the entire alternative lending space. […] It is a complicated market and a solution that brings together all information and stakeholders onto a single platform is highly compelling for both lenders & the ecosystem as a whole.”

The fintech lending space has grown rapidly in recent years, but many lenders still rely on legacy systems and manual processes that limit efficiency and scalability. Kennek aims to leverage open banking and data integration to provide lenders with a more streamlined, automated lending experience.

The seed funding will allow the London-based startup to continue developing its platform and expanding its team to meet demand from non-bank lenders looking to digitize operations. Kennek’s focus on the UK and Europe also comes amid rising adoption of open banking and open finance in the regions.

Featured Image Credit: Photo from; Thank you!

Radek Zielinski

Radek Zielinski is an experienced technology and financial journalist with a passion for cybersecurity and futurology.

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Fortune 500’s race for generative AI breakthroughs



Deanna Ritchie

As excitement around generative AI grows, Fortune 500 companies, including Goldman Sachs, are carefully examining the possible applications of this technology. A recent survey of U.S. executives indicated that 60% believe generative AI will substantially impact their businesses in the long term. However, they anticipate a one to two-year timeframe before implementing their initial solutions. This optimism stems from the potential of generative AI to revolutionize various aspects of businesses, from enhancing customer experiences to optimizing internal processes. In the short term, companies will likely focus on pilot projects and experimentation, gradually integrating generative AI into their operations as they witness its positive influence on efficiency and profitability.

Goldman Sachs’ Cautious Approach to Implementing Generative AI

In a recent interview, Goldman Sachs CIO Marco Argenti revealed that the firm has not yet implemented any generative AI use cases. Instead, the company focuses on experimentation and setting high standards before adopting the technology. Argenti recognized the desire for outcomes in areas like developer and operational efficiency but emphasized ensuring precision before putting experimental AI use cases into production.

According to Argenti, striking the right balance between driving innovation and maintaining accuracy is crucial for successfully integrating generative AI within the firm. Goldman Sachs intends to continue exploring this emerging technology’s potential benefits and applications while diligently assessing risks to ensure it meets the company’s stringent quality standards.

One possible application for Goldman Sachs is in software development, where the company has observed a 20-40% productivity increase during its trials. The goal is for 1,000 developers to utilize generative AI tools by year’s end. However, Argenti emphasized that a well-defined expectation of return on investment is necessary before fully integrating generative AI into production.

To achieve this, the company plans to implement a systematic and strategic approach to adopting generative AI, ensuring that it complements and enhances the skills of its developers. Additionally, Goldman Sachs intends to evaluate the long-term impact of generative AI on their software development processes and the overall quality of the applications being developed.

Goldman Sachs’ approach to AI implementation goes beyond merely executing models. The firm has created a platform encompassing technical, legal, and compliance assessments to filter out improper content and keep track of all interactions. This comprehensive system ensures seamless integration of artificial intelligence in operations while adhering to regulatory standards and maintaining client confidentiality. Moreover, the platform continuously improves and adapts its algorithms, allowing Goldman Sachs to stay at the forefront of technology and offer its clients the most efficient and secure services.

Featured Image Credit: Photo by Google DeepMind; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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UK seizes web3 opportunity simplifying crypto regulations



Deanna Ritchie

As Web3 companies increasingly consider leaving the United States due to regulatory ambiguity, the United Kingdom must simplify its cryptocurrency regulations to attract these businesses. The conservative think tank Policy Exchange recently released a report detailing ten suggestions for improving Web3 regulation in the country. Among the recommendations are reducing liability for token holders in decentralized autonomous organizations (DAOs) and encouraging the Financial Conduct Authority (FCA) to adopt alternative Know Your Customer (KYC) methodologies, such as digital identities and blockchain analytics tools. These suggestions aim to position the UK as a hub for Web3 innovation and attract blockchain-based businesses looking for a more conducive regulatory environment.

Streamlining Cryptocurrency Regulations for Innovation

To make it easier for emerging Web3 companies to navigate existing legal frameworks and contribute to the UK’s digital economy growth, the government must streamline cryptocurrency regulations and adopt forward-looking approaches. By making the regulatory landscape clear and straightforward, the UK can create an environment that fosters innovation, growth, and competitiveness in the global fintech industry.

The Policy Exchange report also recommends not weakening self-hosted wallets or treating proof-of-stake (PoS) services as financial services. This approach aims to protect the fundamental principles of decentralization and user autonomy while strongly emphasizing security and regulatory compliance. By doing so, the UK can nurture an environment that encourages innovation and the continued growth of blockchain technology.

Despite recent strict measures by UK authorities, such as His Majesty’s Treasury and the FCA, toward the digital assets sector, the proposed changes in the Policy Exchange report strive to make the UK a more attractive location for Web3 enterprises. By adopting these suggestions, the UK can demonstrate its commitment to fostering innovation in the rapidly evolving blockchain and cryptocurrency industries while ensuring a robust and transparent regulatory environment.

The ongoing uncertainty surrounding cryptocurrency regulations in various countries has prompted Web3 companies to explore alternative jurisdictions with more precise legal frameworks. As the United States grapples with regulatory ambiguity, the United Kingdom can position itself as a hub for Web3 innovation by simplifying and streamlining its cryptocurrency regulations.

Featured Image Credit: Photo by Jonathan Borba; Pexels; Thank you!

Deanna Ritchie

Managing Editor at ReadWrite

Deanna is the Managing Editor at ReadWrite. Previously she worked as the Editor in Chief for Startup Grind and has over 20+ years of experience in content management and content development.

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