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Artificial Intelligence Dominates the Drug Discovery Landscape by USD 14,518.68 Million by 2032

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Artificial Intelligence Dominates the Drug Discovery Landscape by USD 14,518.68 Million by 2032

The global artificial intelligence in drug discovery market has witnessed an astronomical surge, with its size reaching an estimated US$ 1,495.28 million in 2022 and projected to soar to a staggering US$ 14,518.68 million by 2032, boasting an impressive CAGR of 20.08% between 2022 and 2032.

AI Transforming Drug Discovery: A Paradigm Shift

The integration of AI solutions in the clinical trial process has emerged as a game-changer, addressing potential obstacles, slashing clinical trial cycle times, and enhancing productivity and accuracy. In the life sciences industry, the rapid adoption of advanced AI solutions in drug discovery processes has paved the way for groundbreaking developments, facilitating the identification of new compounds, therapeutic targets, and the creation of personalized medications.

AI’s Crucial Role in Drug Discovery Research

Traditionally, drug discovery involves identifying molecules that can specifically bind to a target molecule, often a disease-associated protein. The process includes large-scale screenings, followed by rounds of testing to identify promising compounds. However, the conventional approach can be costly and time-consuming, with the average cost of bringing a new drug to market reaching a staggering US$2.6 billion. The advent of AI systems has introduced unparalleled data processing capabilities to accelerate and optimize drug discovery, potentially reducing costs and increasing the efficiency of the entire process.

Driving Factors for AI in Drug Discovery

The prevalence of chronic diseases globally, with six out of ten adults in the United States suffering from such conditions, is propelling the demand for innovative solutions. AI platforms in drug discovery are becoming a feasible option for gaining insights into the development of medications to treat and mitigate the severity of various chronic diseases, thus driving market growth. The transformative potential of AI in shortening R&D schedules, making drug research more cost-effective, and increasing the likelihood of approval is further fueling the industry’s expansion.

Challenges in AI Adoption

While AI offers immense potential, the global healthcare sector faces challenges such as rising medicine and therapy costs. Access to extensive data is crucial for AI, but obtaining data from multiple providers can result in additional costs. Additionally, the lengthy and costly clinical trial process, coupled with the high failure rate of drug candidates, poses significant challenges. 

Opportunities for Growth

Increased R&D activities and the widespread use of cloud-based services present lucrative opportunities for market growth. Despite initial skepticism, the AI business in biopharmaceuticals is experiencing a resurgence, marked by increased investments and collaborations between pharmaceutical companies and AI entities. The active participation of major pharmaceutical players in AI-related investments is significantly impacting the industry’s expansion, opening new avenues for growth.

The Impact of COVID-19 on AI in Drug Discovery

The COVID-19 pandemic has accelerated the adoption of AI in drug discovery. Organizations worldwide have relied on AI for the identification and screening of existing drugs for the treatment of COVID-19. AI’s ability to discover active substances has played a crucial role in addressing various diseases, making it a pivotal tool during the pandemic. The industry’s response to COVID-19 has showcased the potential of AI-based drug discovery to revolutionize healthcare solutions.

Segmental Outlook

The AI in drug discovery industry is segmented based on type, application, drug type, offering, technology, and end user. Key segments include preclinical and clinical testing, molecule screening, target identification, de novo drug design, and drug optimization. The oncology segment dominates the application sector, reflecting the increasing demand for effective cancer treatments. The technology segment, particularly deep learning, holds a significant share and is expected to grow at a rapid pace.

Regional Dynamics

North America leads the global AI in drug discovery market, driven by the presence of major pharmaceutical and biotechnology companies, robust R&D activities, and substantial investments. Asia Pacific, with a burgeoning demand for effective drug discovery solutions, is poised for significant growth, with several startups actively developing AI solutions for drug research.

Competitive Landscape

The competitive landscape is shaped by major players such as IBM, Microsoft, Atomwise Inc., Cloud Pharmaceuticals, Benevolent AI, and BIO AGE. Collaborations between technology companies and academic institutions are driving the widespread adoption of AI in pharmaceutical research.

Report Source: https://www.towardshealthcare.com/insights/artificial-intelligence-in-drug-discovery

 

supply lending edge coriolis intelligence AI lenders

AI in the Packaging Market To Hit $ 5,375.28 Mn by 2032

The global market for artificial intelligence in packaging is poised for unprecedented growth. This article explores the astounding journey, projecting a remarkable surge from USD 2021.3 million in 2022 to an estimated USD 5,375.28 million by 2032, boasting a robust CAGR of 10.28% during the transformative period of 2023-2032.

The packaging industry is not an exception to how artificial intelligence (AI) is changing various industries. AI has emerged as a game-changer in the packaging industry due to the growth of e-commerce, shifting consumer demands, and the need for effective and sustainable packaging solutions. Numerous aspects of packaging, including design, production, quality assurance, and supply chain optimization, are being revolutionized by this technology.

Riding the Waves: Factors Fueling AI in Packaging Expansion

  1. Technological Advancements Propelling the Momentum

In the ever-evolving realm of packaging, technological strides serve as the driving force behind the exponential rise. AI, with its innovative applications, is reshaping the packaging landscape by enhancing efficiency, accuracy, and adaptability.

  1. CAGR Unveiled: A Closer Look at Compounded Annual Growth

Delving into the numbers, the Compound Annual Growth Rate (CAGR) of 10.28% acts as the heartbeat of this thriving market. This steady ascent signifies sustained progress, highlighting the industry’s resilience and adaptability over the forecasted decade.

AI is greatly enhancing the packaging industry’s manufacturing procedures. Intelligent systems with computer vision capabilities can quickly and accurately find flaws or inconsistencies in packaging materials. This prevents waste and lowers the possibility of product recalls by guaranteeing that only high-quality packaging reaches the market. AI algorithms can also optimize packaging arrangements, maximizing material use and reducing excess packaging, which results in cost savings and improved sustainability.

AI is also advancing the packaging industry’s efforts to be environmentally friendly. Companies are increasingly looking for eco-friendly packaging solutions as environmental concerns rise. AI algorithms can evaluate the ecological effects of various packaging materials, assisting businesses in selecting environmentally friendly packaging options. AI can help packaging designs be optimized to use the least amount of material while maintaining product integrity, resulting in less waste and a smaller carbon footprint.

Unveiling the Future of Packaging Inspection: Exploring AI-Powered Vision Systems

Artificial Intelligence (AI) has been playing a significant role in driving sustainable packaging practices. One notable example is the application of AI by Amazon to optimize packaging and reduce product damage. Leveraging a machine learning model, Amazon analyses real-world customer complaint data to identify patterns and improve packaging materials for various products purchased through their online platform.

The Packaging Industry is Being Revolutionized by Artificial Intelligence

The packaging industry is changing due to artificial intelligence (AI), fuelled by several important factors. The adoption of AI technologies is a result of the increased demand for effective packaging solutions caused by the growth of e-commerce. Intelligent algorithms improve order fulfilment accuracy and waste reduction in e-commerce fulfilment centers’ packaging processes. Incorporating AI in packaging is also influenced by shifting consumer demands and preferences. AI algorithms analyze consumer data to create personalized packaging experiences and increase brand loyalty. Concerns about sustainability are pushing businesses to use AI to improve packaging designs, use less material, and have a more negligible environmental impact.

The Role of the Food and Beverage Industry in Propelling Future Innovations

The food and beverage industry represents a significant artificial intelligence (AI) adoption market. This sector is fuelled by robust expansion in emerging markets like Asia Pacific, Africa, and Latin America.

Within this rapidly evolving market landscape, AI technologies offer valuable opportunities for optimizing supply chain management. By enhancing tracking capabilities throughout the supply chain, AI enables companies to elevate product quality control measures before reaching customers. This facilitates improved monitoring, traceability, and overall visibility, enhancing efficiency and customer satisfaction.

North America’s Continued Dominance in the Global Market: Projections and Outlook

Between 2023 and 2032, North America is projected to maintain its dominance in the global market. The region’s growth is propelled by the rising adoption of AI technologies within the packaging industry and the establishment of collaborative efforts between public and private entities to introduce cutting-edge machinery. The convergence of high-end technologies like artificial intelligence (AI) and the Internet of Things (IoT) has garnered significant interest across various industrial sectors, driving increased demand for advanced packaging solutions among integrated device manufacturers (IDMs) and foundry suppliers.

Machine Learning Takes the Lead in Uncovering the Fastest-Growing Market Segment in the AI Landscape

The market for artificial intelligence (AI) in packaging is segmented into machine learning (ML), machine vision, and other categories. Among these segments, ML is projected to experience the highest growth from 2023 to 2032. This growth is primarily driven by the increasing demand for ML in various areas such as data labelling, process automation, and content inspection within product quality assurance and quality control (QA/QC) processes. Ensuring accurate labelling of products is crucial to avoid inspection failures, customer dissatisfaction, and potential profit loss.

Unleashing the Potential: AI-Powered Recycling Systems Transforming Packaging Sustainability

Both consumers and manufacturers have become increasingly aware of the ecological consequences of improper material recycling practices. With the world producing over 2.1 billion tons of garbage annually, only about 16% is being recycled. This alarming statistic highlights the urgent need for concerted efforts to improve recycling rates and reduce the environmental impact of waste accumulation.

As sustainability becomes a key focus for businesses and individuals alike, proper material recycling is gaining prominence. Recognizing the ecological cost of neglecting responsible recycling practices, stakeholders are actively seeking innovative solutions to tackle this global challenge. From a business perspective, embracing efficient and effective recycling strategies aligns with environmental goals and enhances brand reputation and consumer trust.

Comparative landscape

The comparative landscape of Artificial Intelligence (AI) in the Packaging Market comprises various players that contribute to developing and adopting AI technologies in the packaging industry. Market leaders in this landscape are established companies with a strong market presence, advanced AI technologies, and a wide range of AI-enabled packaging solutions. These companies set industry standards and drive innovation in the market. On the other hand, emerging startups bring fresh ideas and unique approaches to packaging automation, optimization, and customization, focusing on niche markets or specific packaging applications. Technology providers specialize in developing and providing AI tools, platforms, and software solutions for the packaging industry, offering AI algorithms, machine learning models, computer vision systems, and data analytics tools. Packaging equipment manufacturers integrate AI capabilities into their machinery to enhance performance, reliability, and automation. Research and consulting firms provide market analysis, strategic insights, and advisory services related to AI adoption in packaging. Collaborative partnerships between packaging companies and AI technology providers aim to combine packaging expertise with AI capabilities, fostering knowledge exchange and mutual innovation.

Key Market Players

  • SIG Combibloc
  • Tetra Pak
  • Stora Enso
  • Metsä Board
  • Ardagh
  • Sealed Air
  • Mondi
  • Berry Global
  • WestRock
  • Verallia
  • DS Smith
  • Georgia-Pacific. Amazon
  • Microsoft
  • GE Digital
  • ABB
  • Otto Motors
  • Universal Robots
  • Clarifai
  • Neurala

Report Source – https://www.towardspackaging.com/insights/artificial-intelligence-in-packaging-market

storage AI

Revolutionizing Warehousing: From Ancient Storage to AI-Driven Efficiency and Innovation

Introduction

The warehousing industry has undergone a remarkable transformation over the years, evolving to meet the ever-changing demands of global trade. In this article, we will explore the history of warehousing, types of warehouses, the types of products being stored today, and fundamental advances such as refrigeration, container shipping, and the rise of e-commerce. We’ll also delve into the modern era of warehousing, the role of computers and specialized software, the impact of artificial intelligence (AI), and future trends in warehouse automation.

A brief history of storage

Warehousing has a rich history dating back to ancient civilizations, when goods were stored in rudimentary facilities. The Industrial Revolution marked a turning point, with the introduction of more organized and specialized storage facilities. The arrival of the railroad and interstate highway system further revolutionized the industry by improving transportation and connectivity.

Types of Warehouses

Warehouses come in various forms, including:

  • Public Warehouses: Facilities that provide storage space to multiple clients on a rental basis.
  • Private Warehouses: Owned and operated by a single entity, generally for its own storage needs.
  • Distribution Centers: Focused on the efficient distribution of products and order fulfillment.
  • Cold Storage Warehouses: Specialized facilities for the storage of perishable and pharmaceutical products.

Types of goods that are stored today

Modern warehouses house a wide range of products, including:

  1. Consumer Goods: Electronics, clothing and household products.
  2. Perishables: Food, pharmaceutical products and medical supplies.
  3. Automotive Parts: Engines, tires and other components.
  4. E-Commerce Inventory: Products sold by online retailers.
  5. Industrial Equipment: Machinery, tools and raw materials.

Innovative points in storage

  1. Invention of Refrigeration: Refrigeration technology allowed the storage of perishable products and the expansion of the food industry.
  2. Oil and gas pipeline transportation: Efficient pipelines and storage facilities transformed the energy industry.
  3. Invention of container shipping: Standardized shipping containers revolutionized global trade by simplifying cargo handling and reducing costs.
  4. Rise of e-commerce: The exponential growth of online retail required adjustments in warehousing to accommodate order fulfillment, returns, and fast shipping.

The modern era of storage

Today, the storage industry relies heavily on technology and innovation. Computers and specialized software are essential to optimize storage and distribution processes. The four main types of software used in the storage industry include:

  1. Warehouse Management Systems (WMS) – Streamlines inventory management, order processing, and pick-and-pack operations.
  2. Transportation Management Systems (TMS): Facilitate efficient transportation planning and route optimization.
  3. Inventory Management Software – Track stock levels, replenish inventory, and reduce carrying costs.
  4. Supply Chain Management (SCM) Software: Improve overall supply chain efficiency and coordination.

Featured Storage Software Examples

  1. SAP Extended Warehouse Management (EWM): offers comprehensive warehouse and distribution management.
  2. Oracle Warehouse Management (WMS): Optimizes inventory and labor productivity.
  3. Blue Yonder (formerly JDA Software) – Provides end-to-end retail and supply chain solutions.
  4. Manhattan Associates: Specializes in warehouse and transportation management.
  5. HighJump (now part of Korber) – Offers a suite of supply chain management solutions.

Use of AI in the storage industry

Artificial Intelligence (AI) is making significant advances in warehouse industry, with usage terms including:

  1. Predictive analytics: AI analyzes historical data to forecast demand, allowing for better inventory management.
  2. Warehouse automation: AI-powered robots and autonomous vehicles improve efficiency and reduce labor costs.
  3. Staff training: AI-powered simulations and virtual reality help train workers more effectively.
  4. Shipment Tracking: AI enables real-time tracking and monitoring of goods during transportation.

Benefiting from AI service companies

AI company can help warehouses implement AI solutions. We offer expertise in AI technologies, development of custom AI models and integration into existing systems, leading to optimized operations, cost savings and increased accuracy.

Predictable future trends in automation

The future of storage will see greater automation and efficiency, with trends such as:

  1. Robotics: More robots and Automatically Guided Vehicles (AGVs) will help in picking, packing and transportation.
  2. IoT Integration: Internet of Things will provide real-time data to improve inventory and asset tracking.
  3. AI-driven decision making: AI will play a critical role in optimizing warehouse operations, from demand forecasting to
  4. Sustainability: The warehouses will focus on energy efficiency and sustainable practices to reduce their environmental footprint.

Conclusion

The warehousing industry has evolved significantly, adapting to the changing landscape of global commerce and e-commerce. Today, technology and software solutions, combined with the power of AI, are ushering in an era of efficiency, precision and innovation. As warehouses continue to automate and optimize their operations, they are prepared to meet the challenges and opportunities of the future, revolutionizing the logistics and supply chain landscape.

reuters

Thomson Reuters Introduces Cutting-Edge AI and Automation Features to Transform Tax and Audit Processes Globally

Thomson Reuters, the renowned global content and technology company, has unveiled a series of updates to its tax, accounting, and audit products at its annual customer event, SYNERGY. The enhancements across SurePrep TaxCaddy, Cloud Audit Suite, and ONESOURCE aim to automate tax workflows, bringing increased efficiency and time savings for professionals in firms and multinational corporations. Notably, Thomson Reuters is integrating generative AI capabilities into its tax products, such as Checkpoint Edge and ONESOURCE Global Trade Management.

Piritta van Rijn, Head of Accounting, Tax & Practice at Thomson Reuters, emphasized the challenges tax industry professionals face due to the rapid pace of regulatory changes and hiring difficulties. The newly introduced capabilities leverage AI to automate tax preparation, allowing professionals to focus on client service, business growth, and cultivating better workplaces.

SurePrep TaxCaddy, a key component of Thomson Reuters’ tax product suite following the acquisition of SurePrep, is set to launch auto-categorization capabilities within its intuitive client portal. This feature simplifies document and data gathering, enabling taxpayers to upload multiple documents seamlessly. The incorporation of AI and machine learning technology will auto-categorize these documents, streamlining the review process for tax professionals. The auto-categorization feature is expected to be available to US customers in 2024.

To address the challenge of auditing large volumes of data, Thomson Reuters will introduce ‘smart analysis’ capabilities in Cloud Audit Suite. This enhancement will apply AI to streamline data ingestion, identify potential anomalies, and automate testing and confirmations, thereby improving efficiency and quality throughout the audit process. The smart analysis feature is in beta in the USA starting November 2023, with general availability scheduled for 2024.

The Checkpoint Edge AI Assistant, currently in beta in the USA and set for general availability in 2024, utilizes generative AI to assist tax and accounting professionals in tax research. This tool accelerates the orientation to tax topics and facilitates quicker access to answers, utilizing trusted content with credible citations.

Thomson Reuters is also addressing the compliance needs of multinational corporations with new capabilities in the ONESOURCE suite. The integration of generative AI technology into ONESOURCE Global Trade Management will expedite product classification and mapping for corporate tax and trade professionals, ensuring compliance with changing regulations across multiple countries. Additionally, the ONESOURCE E-Invoicing, now generally available globally, simplifies compliance with electronic invoicing regulations in over 80 countries.

Ray Grove, Head of Corporate Tax and Trade at Thomson Reuters, highlighted the significance of these capabilities in automating compliance around global minimum tax requirements and simplifying e-invoicing. These developments are poised to be game-changers, allowing corporations to build their businesses and support customers while confidently meeting global compliance obligations. Thomson Reuters continues to be at the forefront of innovation, providing comprehensive solutions to navigate the evolving landscape of tax and audit processes worldwide.

procurement

How to Adapt Procurement Skills in the Era of AI Innovation

The age of artificial intelligence (AI) is here. It’s not a question of if AI will change the industry, but one of when and how. As this shift approaches, employees and leaders alike must prepare for the impact of AI in procurement.

AI will become more common in procurement, changing what skills are most important in the industry. Those who can get ahead of that trend could thrive over the coming years, while those who don’t may fall behind.

The Impact of AI in Procurement

AI’s impact on procurement will be significant. Digitization remains the second most-cited procurement strategy today, and analytics and robotic process automation are the most deployed and value-driving of these investments.

Analytical applications are the most promising in procurement circles. AI can compare multiple suppliers to identify the best one for each job faster and more reliably than humans. Alternatively, it could analyze spending patterns to highlight cost inefficiency and find new ways to save.

The rise of AI in procurement also has significant implications for compliance and risk management. Machine learning models can automate regulatory assurance tasks to ensure all forms meet applicable standards or alert managers to compliance issues with supply chain partners. Similar tools can look for supply chain risks to inform better decision-making.

Automating repetitive tasks is another key use case for AI in procurement. Models can manage billing, data entry, basic outreach, summarizing feedback and similar time-consuming tasks to give employees more time. Businesses can then accomplish more, even without a larger workforce amid labor shortages.

Preparing for an AI-Driven Future

Because there are so many use cases for AI in this field, the procurement workforce will shift in response. The skills employees need to succeed will change, so it’s important to prepare for this shift.

Learn to Work With AI

The most important part of that adaptation is learning to work with AI. That’s crucial both for effective AI implementation and remaining competitive as a worker.

AI is impressive, but it’s only a tool. Procurement operations need people who know how to use it properly to experience all its benefits. At the same time, 51% of IT decision-makers say they lack the in-house talent to meet their AI goals. That leaves both an opportunity and a challenge for the procurement workforce.

If more existing employees learn general AI skills, businesses wouldn’t have to scramble to find outside talent. Workers who pursue this career development would also better their chances at employment and promotion in the future. That skills shift will take time, but it’ll be worth it long term for everyone involved.

Foster Tech Talent

Procurement professionals can take this trend further. As AI grows, so will the other technologies that support it, like digital data, cloud computing and the Internet of Things (IoT). Employees who get more familiar with tech will be better suited to thrive in these more tech-centric environments.

Automation through AI will leave employees with more time but fewer of the same tasks to complete. Consequently, they’ll have to perform different roles. Making sure all the company’s new technology works as it should is one of the most crucial of these roles.

The shift to tech talent lies on both employer and employee. Employers can provide upskilling opportunities to foster these new skills and employees can pursue them on their own time to get ahead of the trend.

Emphasize Strategy, Communication and Creativity

Previously, humans had to do much analytical work to find the best procurement options. Open tendering was the most transparent but most time consuming, so employees had to be able to make complex choices quickly. AI in procurement removes that inefficiency barrier and automates decision making, so the same skills won’t be as in demand.

In the age of AI, it’ll be more important to be strategic, communicative and creative. AI can handle analytical, efficiency-focused tasks, so it’s up to employees to find ways to apply its insights effectively.

Real-world implementation, communicating with other stakeholders and finding creative solutions based on data aren’t strong suits for AI. However, humans excel at them. Consequently, the workforce of tomorrow will center around these skills while AI manages the administrative and analytical side.

Cultivate Soft Skills

As procurement professionals develop these new talents, they shouldn’t overlook soft skills. Job-specific hard skills were more important in the past, but as AI changes jobs, businesses will need people who can adapt amid the shuffle. Soft skills are the key to meeting that demand.

People skills are some of the most crucial of these talents for procurement. As AI handles more of the paperwork, employees will likely need to spend more time on maintaining supplier relationships. Being personable and a good communicator is essential for that role.

Developing these soft skills also gives employees an edge AI can’t beat. That’s hard to ignore amid rising fears of job displacement as AI automates more roles.

Apply AI and Human Talent Where They Fit Best

Those fears over job loss deserve more attention. In a perfect world, AI in procurement will help human workers do their jobs more efficiently, not replace them. However, it can be tempting to automate some roles entirely to save money.

Replacing humans with AI may seem profitable, but it’s not ideal for anyone in the end. AI has several significant risks that could endanger procurement workflows that rely too heavily on it. The best solution is to learn AI and humans’ distinct talents, and distribute tasks accordingly.

AI is great at data-heavy, repetitive and analytical tasks, whereas humans are better at roles requiring adaptability or intrapersonal communication. As the workforce shifts in response to AI, employees should focus on developing the latter to solidify their value. Employers should note this distinction and view AI as a complement to people, not a replacement.

It’s Time to Adapt to the Age of AI in Procurement

Jobs and their required skills have always shifted as new technologies have emerged. The difference with AI is this change could happen much faster than previous innovations.

Employers and employees alike must get ready for the changes AI in procurement will bring. If they can adapt early, they can ensure AI and the workforce work together to achieve optimal results.

mecalux

Mecalux and Siemens Unveil AI-Driven Robotic Order Picking System for Optimized Warehousing

Mecalux, in collaboration with Siemens, has introduced an advanced solution to revolutionize order picking in warehouses and logistics centers, leveraging the power of artificial intelligence (AI) technology.

Developed at Mecalux’s technology center in Barcelona, Spain, this cutting-edge collaborative robotic picking system is set to enhance order fulfillment processes.

Key Highlights:

1. Siemens’ AI Technology Integration: Mecalux’s new robotic picking solution integrates Siemens’ groundbreaking SIMATIC Robot Pick AI technology, which relies on deep learning algorithms to automate and streamline the order picking process. With AI embedded into the programmable logic controller (SIMATIC S7-1500), the collaborative robot (cobot) operates autonomously and with unparalleled precision.

2. Strong Alliance: This innovative solution is the result of a robust partnership between Mecalux and Siemens, combining their expertise in industrial automation technologies. Their long-standing collaboration has enabled the creation of technology solutions to address the challenges faced by the logistics industry.

3. Versatile Solutions: Mecalux offers two collaborative picking solutions. The first is a cobot designed to work safely alongside human operators, and the second is an automated system that operates independently in high-performance pick stations.

4. High Efficiency: Developed to operate around the clock, the Mecalux system can execute up to 1,000 picks per hour, making it suitable for businesses across various sectors seeking to optimize their order processing.

5. Smart Vision System: A camera positioned above the cobot’s picking box captures a 3D image of the items, facilitating order preparation. The AI algorithm, trained on millions of items, makes split-second decisions to identify collision-free picking positions for items, even with complex shapes. Importantly, it doesn’t require prior knowledge of the 3D model of the items, thanks to the advanced artificial intelligence algorithm.

6. Precision and Adaptability: The cobot precisely deposits the selected items into the picking box, making the most efficient use of space. Mecalux has designed an algorithm to ensure the items are placed correctly.

7. Dynamic Gripping System: Guided by Mecalux’s warehouse management software, the collaborative picking system can automatically adapt its gripping mechanism to suit the type of merchandise it handles. When presented with a new box, Siemens’ vision system and AI algorithm identify the items inside and determine the most optimal way to pick each product.

8. Advanced Hardware Platform: Siemens employs its robust S7-1500 PLC range, along with the TM-MFP (Technology Module-Multifunctional Platform), to execute AI technology, all while maintaining stringent cybersecurity standards and utilizing the SCALANCE X family of intelligent switches.

This collaborative picking system signifies a significant stride towards operational efficiency in warehouses and logistics. Mecalux and Siemens are steadfast in their commitment to delivering cutting-edge technological solutions that benefit their clients and elevate the standards of warehousing and order fulfillment.

emission drive battery fleet

The Effects of AI on Fleet Management

AI or artificial intelligence is buzzing in just about every industry. It is greatly changing the trucking industry, from driving to office resources. This article will discuss the future of transportation, AI in the trucking industry, and fleet intelligence.

Future of Transportation

Artificial intelligence is changing the future of transportation in many ways. There are several upcoming trends and new ways of transportation on the horizon. It is as if the Jetsons had the future of technology and transportation right all along. It is time to embrace the future of transportation as we know it. Here are some vehicles that may be just around the corner and some may be a bit further away.

Delivery drones

Delivery drones are unmanned aerial vehicles designed to distribute lightweight packages in the last-mile delivery process. AI is used to autonomously drive the delivery drones or they are remotely controlled. These vehicles are rechargeable, flying robots that can navigate routes and drop-off points. They use GPS, sensors, and computer vision systems to help with navigation. The first commercial drone delivery in the United States took place in 2016. It transported frozen slurpees, donuts, coffee, and chicken sandwiches. Delivery drones are available abroad now and deployed in select US cities.

Driverless vehicles

Driverless or self-driving cars are operated autonomously without human input. There are sensors throughout the vehicle that enable the car to be aware of its surroundings. There are several mapping tools used to operate driverless vehicles. These include cameras, radar, LiDAR, ultrasound or sonar, GPS, odometry, and inertial measurement units. These tools work together to compute a three-dimensional model of the vehicle’s surroundings. They inform the vehicle of traffic controls, merging opportunities, and obstacles en route. 

Flying hotel pods

Flying hotels are only a theory at this time. Flying hotels are aircraft designed to remain in flight while housing passengers for an extended stay.  Guests could check in to their own pods and have access to common areas in the facility. Flying hotels can be thought of as a sort of cruise ship in the clouds or low-orbit, traveler-friendly space station. 

Flying taxis

Flying taxis or air taxis are small commercial aircraft that can transport passengers regionally on demand. These aircraft would be used for short-distance commutes. This would be a faster method of transportation because it would bypass any ground traffic congestion. Flying taxis are the perfect candidate for all-electric, zero-emissions air travel, with the first generation of battery-powered planes likely to serve as airport transit services, cargo vehicles, and training planes for new pilots.

Hyperloop

A hyperloop is a high-speed, ground-level transportation system that uses magnetic levitation and electromagnetic propulsion to transport passengers or goods through a vacuum tunnel at jet-like speeds. It is essentially a futuristic train. A hyperloop is composed of three parts which include sealed, low-pressure tubes, pressurized coach pods, and terminals. 

AI in the Trucking Industry

Managing a fleet can be tricky. Managers are required to wear multiple hats and juggle responsibilities and tasks. AI has made this job much more streamlined and efficient. There are many benefits of AI fleet management software. 

Real-time analytics

Real-time analytics is essential to having a smoothly operating fleet. Data is collected and analyzed in real time. This includes your vehicles’ location, status, and movement. AI fleet management systems can monitor your vehicles in real-time and identify potential issues, improve fuel efficiency, and even detect vehicle misuse. When a problem is detected it can alert you so you can immediately take corrective actions.

Vehicle maintenance 

You do not have to wait for a vehicle to show signs of breakdown. Using AI algorithms, you can analyze vehicle use patterns and real-time data from sensors installed in vehicles. This is helpful in identifying small signs of wear and tear before they become bigger, more expensive problems. Also, AI software can help prevent breakdowns and reduce the risk of accidents on the road.

Route planning  

Route planning can become overwhelming. This is especially true when you are managing a large fleet. There are many factors to consider including traffic patterns, weather conditions, and vehicle availability, to ensure your vehicles operate efficiently and on time. AI can analyze real-time data from various sources, such as GPS trackers and weather and traffic alerts, to automatically optimize routes for maximum efficiency.

Driver safety management

Driver safety is the top priority for many fleet managers. However, monitoring and improving driver behavior while staying on top of other fleet tasks can require a massive amount of effort. AI-powered telematics devices, such as dash cams and speed sensors, can automatically record, detect, and alert you to unsafe driving behaviors such as speeding, harsh braking, and distracted driving. 

Dashcam video analysis

Dash cams are a way to monitor a driver’s behavior. This protects your drivers against false incident claims and ensures compliance with safety regulations. You can use AI-powered dash cam software which can automatically flag and categorize footage relevant to unsafe driving behavior. This allows you to review your driver’s performance more easily and gives you insight into the kind of training you need to provide.

Fleet Intelligence 

Artificial intelligence is revolutionizing the trucking industry. Telematics devices can be installed in the vehicles and make accurate predictions based on the data collected. Some telematics devices include GPS trackers, dash cams, and sensors that can provide a wealth of information on your vehicle’s status, including data on its movement, speed, location, and fuel consumption.

Fleet intelligence is a cloud-based fleet management solution designed for heavy equipment fleet operators and managers. Key features include an automated maintenance scheduler, layered map views, asset tracking, and real-time alerts.

Fleet intelligence allows managers to monitor their entire fleet in real time and in one place. It provides critical data such as location, DTC alerts, geofencing, oil scans, and preventative maintenance issues.  Fleet intelligence can also identify and reassign underutilized machines, automate maintenance schedules, and analyze the fleet by job, timeframe, foreman, and location.

Fleet intelligence software can send messages and alerts to mobile devices to track vehicles. It can do an oil scan, geofence, and other related events in order to track vehicles.  Also, a support team is available so users can submit tickets online for any support inquiries or reach out to the support team via phone and email.

Finally, AI is rapidly changing and transforming fleet management. With AI’s ability to collect and analyze vast amounts of data, it is making the industry even more efficient. AI will only continue to transform how fleets are managed.

SMB business

AI Stats and Trends for Small Business Marketing

Small businesses (SMBs) are a busy bunch. On any given day, they might be fulfilling orders, engaging with customers in-person, managing staff, doing their books — plus dozens of other tasks. Most would relish an opportunity to gain back an extra hour, or save some extra money.

Luckily, those goals (and others) are attainable thanks to artificial intelligence (AI) and marketing automation. These technologies can help small businesses work more efficiently, drive more sales, and improve the ways they are marketing themselves – without making it more of a headache or a time suck.

We recently published a report at Constant Contact called, Small Business Now: An AI Awakening, that outlines how SMBs are thinking about AI and automation, and some of the results that early adopters are seeing. With insights from nearly 500 small businesses across the U.S., the study reveals how these technologies can enhance marketing effectiveness and help SMBs save time and money. 

If you’re curious about how AI can impact your business, here are the 10 stats about AI that you should know.

Challenge Accepted: 60% of SMBs say their biggest challenge is attracting new customers, while 39% say it’s marketing to their target audience.

Peaked Interest: 74% are interested in using AI or automation in their business, and 55% reported that their interest in using these technologies grew in the first half of 2023.

Off to the Races: 26% are already using AI or automation, and the top use cases are social media (52%), generative content creation (44%) and email marketing (41%).

Proven Success: 91% of the small businesses polled say AI has helped make their businesses more successful.

Reaping the Benefits: 60% of small businesses that currently use AI or automation in their marketing say they have saved time and are working more efficiently.

First step, Social Media: SMBs say the easiest places to start leveraging AI technology are social media, content creation, and analytics.

Financial Gains: 28% of SMBs expect AI and/or automation to save them at least $5,000 in the next year.

Increasing Efficiency: 33% of small businesses estimate they have saved more than 40 minutes per week on marketing by using AI or automation.

Top Concern: 44% of small businesses noted data security as their top hesitation about using AI.

Value Recognition: The more SMBs use AI, the more they value it.  70% of SMBs would be willing to pay more to access AI and automation. 

So, what do all these stats mean? I’m glad you asked.

AI is here to stay. The small businesses who are currently using tools powered by AI overwhelmingly agree that it is making their businesses more successful. They are working more efficiently, saving money, improving customer experiences, and growing quicker.

So, if you’re an SMB who is either starved for more time in your week, or you want to improve the way you engage with your customers without adding extra marketing work to your plate, don’t write off AI as a passing trend. Give it a try and you might be surprised about the results you see.

About the Author

Dave Charest is the Director of Small Business Success for Constant Contact, a digital marketing and automation platform that has helped millions of small businesses and nonprofits become better marketers.

AI

Disruption and Transformation: How AI will Impact Global Trade in the Next Decade

The use of artificial intelligence (AI) to sift through data and find areas for improved efficiency has already started to have an impact on the scheduling, safety, and monitoring of shipments from ports to railways.  Major players in the shipping market have been investing in AI capabilities and research for years, with Maersk recently opening an AI-driven automation center as a symbol of the type of disruption that can be expected in the market as the promises of technology begin to manifest.  But beyond these immediately tangible gains in efficiencies and minor disruptions that come from early applications of AI to global trade, what are the more substantive impacts that we can anticipate in the next decade?  How will trade in goods and services change?  What changes can we expect in the labor market and costs of doing business?

Trade in goods – what will stop shipping? 

Innovative ideas such as the 3D printing of clothing have moved from science fiction to science fact.  The use of 3D printing is a daily reality for designers, and the use of such technology is only picking up pace as companies respond to the criticism of how ‘fast fashion’ is unsustainable.  This is just one of the many items which may no longer be imported into the U.S. as AI and new technology create alternative production sites.  Soon it may be unnecessary to ship everything from phone cases to toys, since they can be manufactured at a continuously lower cost in local facilities or even consumers’ homes.  The use of AI will even improve yields from hydroponic and traditional farms, suggesting that many food products would no longer make sense to ship from distant locations. If AI and new technology can’t (yet) create unique products such as rare earths, new and developing tools will still have an impact on trade patterns, as they can help find untapped resources that are in friendlier locations.  With the U.S. government funding AI-based research to improve the country’s ability to produce key products such as energy storage devices, more and more of those products and the resources that go into them will be produced domestically. The bottom line is that the usage of AI and new technology over the next decade will not only bring dramatically improved logistics, it will shift what is moved from place to place as a substantial portion of goods are suddenly competitive even when produced domestically.

Trade in services – major impact from AI

From market research to IT and customer service support, AI applications are already replacing many low and medium-complexity outsourced service jobs around the globe. While there is still a strong business case for leveraging global talent pools outside of high-cost markets such as the U.S., the overall trade in services is going to likely dip as more of these service requirements are handled by AI in domestic markets.  Reinforcing this trend are increasing concerns over data privacy regimes and cyber security, which will incentivize business to keep valuable information and personnel and customer details fenced off in their domestic markets.  Generative AI is also likely to reduce royalties and license fees as customers find it easier to produce everything from wall art to new music through free applications.

How AI will impact jobs and costs

The ongoing automotive union strike and recent picketing by writers in Hollywood are both related to how AI usage and new technology are threatening traditional industry jobs.  Tensions have been simmering for decades as longshoremen and freight workers worry that automation may take over many of their tasks. These types of struggles will continue for years, but the adoption of this technology will be inevitable in the U.S. in order to stay competitive with early adopters of automation in Asia and Europe as well as low-cost labor in other parts of the world.  In the next ten years, there will need to be substantial public-private joint efforts (and investments) to cross-train workers into higher-complexity positions in recognition of this technological transformation.  

The loss of traditional jobs is clearly not limited to the logistics sector – as seen from concerns voiced from visual artists, finance experts and even attorneys that they are losing work to new generative AI tools.  The solutions to this shift in labor will also have to be broad-based, to include transforming educational systems to better prepare future employees for the working world that awaits them.  The World Economic Forum suggested that over a billion jobs will be impacted or displaced as a result of improved AI technology and that higher education needs to be changed accordingly.  However, many of the jobs that will be impacted do not require college degrees, so the real challenge is to prepare students from the elementary level for jobs that don’t yet even exist, and for an economy where many existing labor roles will be defunct.

When it comes to costs, AI’s most immediately attractive benefit is efficiency. In global trade, there will be substantially more automation of transportation and a reduction in the requirement for warehousing as forecasting models render the requirement to have supplies in backstock unnecessary.  Companies will be able to reduce staff and service costs using automation and generative AI.  However, not all costs will go down.  The expense for data centers and cyber security will potentially rise substantially as companies put more reliance on their technology tools to run business operations and sort through the universe of data necessary to improve forecasting capabilities.  Many of the savings in labor costs will likely need to be plowed into IT support and maintenance costs.  Nevertheless, AI usage offers tremendous savings in efficiencies and improved safety across all business sectors, which will drive broad-based adoption of new technology across all business sectors.

Buckle up for an interesting ride

The next decade will bring such widespread change that it can be hard to determine what path trade will wend among the geopolitical and technology changes that shape global business.  A few trends are clear, however: automation will increase, AI applications are going to proliferate into all business sectors, and only agile, informed companies will succeed in this volatile environment.  The cost of early adoption and implementation of some of the new technologies that are arising out of AI applications can be daunting, but keeping a sharp eye on developments in the market has never been more important.  Most U.S. businesses are already using AI in some form or another, and an overwhelming percentage of them intend to increase the usage of AI for everything from improving efficiency to handling customer complaints in the years to come.  When taken together with the impressive strides forward in automation, 3D printing, virtual reality tools and blockchain technology, it is crucial for companies to invest time and resources into forecasting and planning for substantial changes.  The advantage is that now they can leverage AI to do it faster and more efficiently.

Kirk Samson is a Senior Director of Business Process Management at the global consulting firm Nexdigm and a Director at the International Trade Association of Greater Chicago.

generative AI market platform edge

Edge AI Market Poised to Reach $70 Billion by 2032: Unleashing the Power of Decentralized Intelligence

In a world increasingly reliant on data-driven decision-making, Artificial Intelligence (AI) has emerged as the linchpin of technological advancement. One of the most transformative facets of AI is Edge AI, which brings the processing power of AI algorithms closer to the data source. This paradigm shift has not only accelerated the pace of innovation but also opened up new horizons for industries across the board. Recent market research indicates that the Edge AI market is set to explode, with projections estimating a worth of $70 billion by the year 2032.

The Edge AI Revolution

Edge AI represents a quantum leap in the evolution of AI applications. Unlike traditional AI models that rely on cloud computing for processing, Edge AI shifts the computational burden to local devices or on-premise servers. This decentralized approach not only reduces latency but also enhances privacy and security, making it ideal for real-time applications like autonomous vehicles, industrial automation, healthcare, and more.

 Factors Driving Edge AI Market Growth

  1. Real-time Decision Making: Industries such as autonomous vehicles, healthcare, and manufacturing require instantaneous processing for mission-critical applications. Edge AI’s ability to make split-second decisions without relying on a distant server is a game-changer.
  2. Data Privacy and Security: With an increasing emphasis on data privacy and stringent regulatory frameworks, Edge AI offers a compelling solution. By keeping sensitive information on-premise, it mitigates the risks associated with transmitting data to the cloud.
  3. Bandwidth Optimization: Edge AI alleviates the strain on network bandwidth by processing data locally. This is especially crucial in scenarios where transmitting large volumes of data to the cloud is impractical or cost-prohibitive.
  4. IoT Proliferation: The Internet of Things (IoT) has witnessed explosive growth, and Edge AI is the perfect complement. By embedding AI capabilities into IoT devices, they can make intelligent decisions autonomously, reducing the need for constant connectivity.
  5. Customization and Personalization: Edge AI enables the tailoring of AI models to specific use cases. This level of customization ensures that solutions are finely tuned to the unique requirements of different industries and applications.

Verticals Poised for Disruption

  1. Autonomous Vehicles: Edge AI is a linchpin in the development of self-driving cars. Real-time processing is vital for making split-second decisions in complex traffic scenarios.
  2. Healthcare: From wearable devices to medical imaging, Edge AI is transforming healthcare by providing faster diagnostics, personalized treatment plans, and even remote patient monitoring.
  3. Manufacturing and Industry 4.0: Edge AI is revolutionizing the manufacturing sector by enabling predictive maintenance, quality control, and process optimization in real time.
  4. Smart Cities and Infrastructure: Edge AI is instrumental in creating intelligent urban environments. From traffic management to energy optimization, it is pivotal in building sustainable cities of the future.