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How AI Efficiently Responds to Rapid Changes in Warehouse Workload

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How AI Efficiently Responds to Rapid Changes in Warehouse Workload


Artificial Intelligence, or AI, has found its application in many industries, including inventory management, supply chain management, and warehousing.

In today’s modern marketplace, led by competitive SMBs and interconnected technologies that link sellers and buyers globally, being able to respond to change quickly is of utmost importance. Companies of all sizes experienced demand fluctuations when the pandemic hit.

This is where AI comes into play to make warehouse operations more efficient, even during unstable supply and demand. Your end goal should be transforming your old-school warehouse into a smart system that does things faster, better, and cheaper.

So, let’s dive right in and look at how AI technology can help your business stay prepared and respond to changes in workload.

1. How AI enhances productivity and accuracy

Until recently, most warehouse operations relied on human labor. However, this leaves a possibility for errors, miscalculations, and inaccuracies. Implementing AI in your warehouse operations saves time and costs, promotes work efficiency, and provides a better customer experience.

As a result, your warehouse will become more productive, and you will improve the accuracy of operations. For instance:

  • Get real-time inventory updates with the help of sensors, smart shelf solutions, and automated inventory management software
  • Use AI chatbots to quickly resolve customer queries with very little human interaction
  • Use robots to support warehouse workflows and handle repetitive or physically-challenging tasks without fatigue
  • Maintain a better speed of operations and output
  • Sort, tag, and scan products with robots for easier management and distribution
  • Reduce errors in fulfillment by synchronizing physical with digital inventory
  • Enjoy better shipping route and delivery planning, resulting in shorter delivery times

The boost in productivity and accuracy of warehouse operations using AI comes from its power of collecting data and automating tasks.

According to a recent HBR research on warehouse automation, 42% of warehouse workers believed automation increases safety, 38% stated that automation makes their jobs faster and more efficient, and the remaining 20% said that automation boosts their quality of work.

These points are important since they show how much automation helps a business when there are sudden and rapid fluctuations in demand and workload. Plus, a nice “side effect” of your efforts to boost productivity with AI is saving costs and preventing unnecessary waste.

2. Automated order fulfillment

The most time-consuming warehouse operations are picking, packing, and fulfilling orders. In this area, the chances of human error are high, and speed is of utmost importance.

Due to the repetitive and manual nature of these tasks, AI can overtake operations and automate processes. To get synchronized results across multiple locations, especially if you’re an omnichannel seller, it’s best to automate both your digital and physical inventory.

You can automate your digital operations with a solid warehouse management system (WMS) to ensure that goods and materials move in the most efficient possible way. Often companies use ERP or TMS systems as well.

On the other hand, some great examples of automating physical order fulfillment operations are IoT helpers such as:

  • Autonomous mobile robots (AMRs) for order-picking
  • Automated guided vehicles (AGVs) for transporting goods
  • Automated sorting systems or conveyor belts

The market for warehouse robots like AGVs and AMRs is expected to reach over $18 billion by 2027. So, companies are starting to use these devices to optimize their warehouse operations and work more efficiently.

Automated order fulfillment will greatly boost the shopping experience of your buyers, ensure speedy deliveries, and drive customer satisfaction and loyalty. Additionally, warehouse robots can also help you become more efficient in dealing with returns management and reverse logistics.

3. Smart and dynamic staffing

No matter how automated your warehouse is, you’ll likely still need human employees. Luckily, HR benefits from AI as well!

In terms of warehouse employees, the main issue arises when sudden changes in warehouse workload leave you understaffed. On the other end of the spectrum, overstaffing will devour your budget. So, this is where AI can help – at the intersection of supply chain management and HR.

For instance, you can use AI-powered logistics staff scheduling software to schedule employees in minutes and assign shifts or find replacements quickly in case of last-minute changes.

Self-learning AI systems use collected data to plan the workforce efficiently based on workload, current demand, forecasted demand, production capacity, appropriate time off and breaks for staff, etc. Additionally, tools like these can improve the efficiency of your routes, delivery planning, and assigning shifts to drivers remotely.

Synchronizing manufactury and delivery staff during fluctuating demand is another issue you can solve with AI-enabled shift scheduling.

On the subject of smart staffing, AI scheduling will also allow you to stay compliant and work according to labor laws and regulations. Parts of this regulation are ensuring equal hours for all employees, paid time off, vacation days and holidays, enough break time between shifts, and similar.

Modern warehouse operations are dynamic, so your workforce staffing solution also has to match!

4. Improved warehouse safety with AI

In times of turbulent demand, warehouse safety is often overlooked. Luckily, this is also an area where AI can help.

For instance, AI-fed IoT sensors can help keep an eye on warehouse equipment, aid the movement of human staff and robots to avoid collisions, warn when machinery is about to break down, and more. Another example is wearable IoT devices that monitor the health of your employees at all times.

Furthermore, according to the National Safety Council Injury Facts:

“Forklifts were the source of 78 work-related deaths and 7,290 nonfatal injuries involving days away from work in 2020.”

So, to prevent or decrease these forklift injuries, you can let AI robots do the heavy lifting. Another solution would be using ADAS (Advanced Driver Assistance System) and computer vision when operating forklifts to increase safety.

Additionally, warehouses can use AI and audio-enabled cameras to detect movement and ensure the safety of their inventory, machinery, and equipment. And, of course, to ensure there are no unauthorized entries in your warehouse, you can use advanced AI facial recognition to grant access to authorized personnel.

Last on the subject of warehouse safety is the importance of warehouse maintenance as the first step to preventing injuries and malfunctions. Look into implementing an AI-powered CMMS system (computerized maintenance management software) to help you stay proactive when dealing with maintenance.

5. Dynamic supply and demand planning

Last but not least, let’s see how you can optimize your supply chain with AI in a way that gets you more accurate projections and forecasts about the expected demand.

One of the main supply chain issues of retailers globally is inaccurate demand forecasting, resulting in high out-of-stock losses. But sourcing a lot more than you can sell is also not the answer. You can get stuck with dead stock if the trend passes and sales don’t go as expected. If this is you, you’re practically leaving money on the table.

Here are ways AI and Machine Learning (ML) can help you avoid problems like out-of-stock and dead stock:

  • Predicting dynamic demand and adjusting the lead times accordingly
  • Using a smart inventory system with RFID tags and sensors to signal low quantities
  • Using robots to scan warehouse aisles and signal low inventory levels (similar to Sam’s Club’s recent inventory robots)
  • Improving sales performance by predictive analysis
  • Figuring out less popular products and decreasing their supply (and the opposite – ensuring there’s always safety stock of the more popular ones)
  • Calculating safety stock more accurately to ensure uninterrupted supply
  • Taking into consideration events like supplier holidays and non-working days, events, promotions, and sales you’re organizing, etc.

How AI can do all of the above lies in its power to analyze large amounts of data that would be impossible to do with other conventional methods. This ability of AI to process, structure, and understand large databases gives it superior predictive power. The more historical data you have available, the better decisions your AI will make.

Wrapping Up

Implementing AI technologies and solutions in warehouse inventory management operations might be a long-term investment, but it will pay off more than you imagine. The initial implementation cost is perhaps the only downside of this technology. But, as we said, with the boost in productivity and warehouse efficiency, AI has an incredible return on investment or ROI.

This is especially true for large-scale retailers and SMBs who collect large amounts of data that they don’t use properly. Here’s where AI shines – gathering, analyzing, and self-learning all about your business and customers to provide you with untapped financial opportunities (think upsells and cross-sells!).

All in all, AI makes it easier for any type of business to scale and become more efficient in its warehouse operations and overall workflows, especially in markets of inconsistent or unstable demand.

Inner Image Credits and Featured Image Credit: Provided by the Author; Thank you!

Rob Press

Rob is a Senior Manager at Deputy, a robust scheduling software that can be used to manage your workforce in a wide variety of different industries. Aside from helping businesses reach operational efficiency, he keeps up to date with the latest trends in SaaS, B2B, and technology in general.

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Fintech Kennek raises $12.5M seed round to digitize lending

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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 tech.eu 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 Kennek.io; 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

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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

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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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