The Future of Supply Chain Automation
As Amazon continues to set the bar for efficiency by integrating an astounding spectrum of automation technology, it’s becoming increasingly apparent that traditional supply chain models are ripe for disruption.
For this reason, companies around the world are now rethinking their warehouse and distribution systems, with automation taking center stage.
Today’s infographic from Raconteur highlights the state of automation across global supply chains, while also providing an outlook for future investment.
Long Time Coming
Let’s start by taking a look at what supply chain technologies are priorities for global industry investment in the first place:
|Rank||Technology||% of Companies* Investing in Tech|
|#3||Internet of things||41%|
|#14||Virtual reality and digital twins||6%|
*Based on survey of supply chain professionals in retail, manufacturing, and logistics fields
As seen above, warehouse automation has already received more investment (55%) than any other supply chain technology on the list, as companies aim to cut delivery times and improve overall margins.
Interestingly, other areas receiving significant investment—such as predictive analytics, internet of things, or artificial intelligence—are technologies that could integrate well into the optimization of supply chain automation as well.
Smoothing the Transition
While fully automated supply chains in most industries may still be a few years away, here is how companies are investing in an automated future today:
|Timeline For Acquiring New Automation Tech||% of Warehouse Managers Surveyed|
|Have, looking to upgrade||8%|
|Within 12 months||10%|
|One to three years||21%|
|Three to five years||8%|
|Over five years||3%|
According to the above data, over 70% have already integrated automation technology, or are planning to within the next five years. On the flip side, over a quarter of warehouse managers are not currently looking to integrate any new automation tech into their operations at all.
Adoption Rates and Growth
As supply chain automation gains momentum and industry acceptance, individual processes will have varying adoption rates.
Take order fulfillment, for instance. Here, only 4% of current operations are highly automated according to a recent survey from Peerless Research Group:
|Order Fulfillment Operations (Picking and Packaging)||Percentage of Respondents|
|A mix of automated and manual processes||42%|
|Mostly or all manual||49%|
Meanwhile, 49% of operations were primarily manual, illustrating potential for growth in this particular area.
It’s worth noting that other individual supply chain components, such as conveyor belts, storage, automated guided vehicles, and shuttle systems, will all have differing trajectories for automation and growth.
Post-COVID Supply Chains
The COVID-19 pandemic has shown us that complex supply chains can become fragile under the right circumstances.
As supply chains see increased rates of automation and data collection becomes more integrated into these processes, it’s possible that future risks embedded in these systems could be mitigated.
Infographic: Generative AI Explained by AI
What exactly is generative AI and how does it work? This infographic, created using generative AI tools such as Midjourney and ChatGPT, explains it all.
Generative AI Explained by AI
After years of research, it appears that artificial intelligence (AI) is reaching a sort of tipping point, capturing the imaginations of everyone from students saving time on their essay writing to leaders at the world’s largest tech companies. Excitement is building around the possibilities that AI tools unlock, but what exactly these tools are capable of and how they work is still not widely understood.
We could write about this in detail, but given how advanced tools like ChatGPT have become, it only seems right to see what generative AI has to say about itself.
Everything in the infographic above – from illustrations and icons to the text descriptions—was created using generative AI tools such as Midjourney. Everything that follows in this article was generated using ChatGPT based on specific prompts.
Without further ado, generative AI as explained by generative AI.
Generative AI: An Introduction
Generative AI refers to a category of artificial intelligence (AI) algorithms that generate new outputs based on the data they have been trained on. Unlike traditional AI systems that are designed to recognize patterns and make predictions, generative AI creates new content in the form of images, text, audio, and more.
Generative AI uses a type of deep learning called generative adversarial networks (GANs) to create new content. A GAN consists of two neural networks: a generator that creates new data and a discriminator that evaluates the data. The generator and discriminator work together, with the generator improving its outputs based on the feedback it receives from the discriminator until it generates content that is indistinguishable from real data.
Generative AI has a wide range of applications, including:
- Images: Generative AI can create new images based on existing ones, such as creating a new portrait based on a person’s face or a new landscape based on existing scenery
- Text: Generative AI can be used to write news articles, poetry, and even scripts. It can also be used to translate text from one language to another
- Audio: Generative AI can generate new music tracks, sound effects, and even voice acting
People have concerns that generative AI and automation will lead to job displacement and unemployment, as machines become capable of performing tasks that were previously done by humans. They worry that the increasing use of AI will lead to a shrinking job market, particularly in industries such as manufacturing, customer service, and data entry.
Generative AI has the potential to disrupt several industries, including:
- Advertising: Generative AI can create new advertisements based on existing ones, making it easier for companies to reach new audiences
- Art and Design: Generative AI can help artists and designers create new works by generating new ideas and concepts
- Entertainment: Generative AI can create new video games, movies, and TV shows, making it easier for content creators to reach new audiences
Overall, while there are valid concerns about the impact of AI on the job market, there are also many potential benefits that could positively impact workers and the economy.
In the short term, generative AI tools can have positive impacts on the job market as well. For example, AI can automate repetitive and time-consuming tasks, and help humans make faster and more informed decisions by processing and analyzing large amounts of data. AI tools can free up time for humans to focus on more creative and value-adding work.
How This Article Was Created
This article was created using a language model AI trained by OpenAI. The AI was trained on a large dataset of text and was able to generate a new article based on the prompt given. In simple terms, the AI was fed information about what to write about and then generated the article based on that information.
In conclusion, generative AI is a powerful tool that has the potential to revolutionize several industries. With its ability to create new content based on existing data, generative AI has the potential to change the way we create and consume content in the future.
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