Whether you are in manufacturing, retail, marketing, healthcare, or business, artificial intelligence and automation practices are starting to shift the way industries operate. A Deloitte study recently found that over 50% of organizations are planning on incorporating the use of AI and automation technologies in 2023. While many top executives are worried about the risks of AI usage, other high-achieving organizations are adopting new tech-savvy operational processes. A survey of Global 500 companies found that leaders choosing to invest in AI and automation business tools and software solutions expect to see significant growth within the next few years. How business practices are expected to change in the new year as artificial intelligence and ... [ ] automation continues to transform business operations.

Today at the Automate 2022 Show and Conference in Detroit, leading experts in artificial intelligence (AI) will discuss how to put AI to use in manufacturing facilities in the keynote panel, "AI & Manufacturing - How Artificial Intelligence is Powering the Next Wave of Manufacturing." Technologists from Accenture, NVIDIA, General Motors, Landing AI and Intel will offer insights and best practices on how businesses can take advantage of AI to enhance their automation processes and improve efficiencies and productivity overall. "The synergies among AI and automation technologies are powering the "These experts will help companies better understand the intricate relationship between robots, automation, and artificial intelligence so decision makers can take advantage of the opportunities presented by smart technologies," said Jeff Burnstein, president of the Association for Advancing Automation, the organizer of the event. "The synergies among AI and automation technologies are powering the next wave of manufacturing, and we want everyone to feel empowered with this knowledge to move forward after Automate." Automate, North America's leading automation trade show and conference, returns to Detroit next week after two decades in Chicago.

How companies can get started with AI The program for our Artificial Intelligence Conference in London is structured to help companies that are still very much in the early stages of AI adoption. Judging by the list of countries putting out policy papers on AI and automation technologies there is very strong interest in AI across the globe. In order to asses the current state of readiness across regions we recently conducted a survey (full report forthcoming) of the state of adoption of machine learning tools and technologies (a lot of what is being currently described as AI is really ML). The survey yielded 11400 respondents including 2000 respondents from Europe: As we assembled the program for our inaugural Artificial Intelligence Conference in London this October we recognized that many companies and organizations around the world are still very much in the early stages of adoption. Anyone wanting to get started on AI technologies will have to wade through an array of methods and technologies many of which are still very much on the leading edge.

The adoption of AI to drive greater automation provides impactful and measurable results, but that doesn't mean it comes without challenges. More often than not, your systems may be dated and not quite compatible with the visions of artificial intelligence dancing in your head. There is also the ongoing concerns that bringing AI and related technologies into businesses, people will be out of work. So, to ensure your organization has fully thought through the future adoption of AI and automation, here are five considerations to start you on the path to success. It goes without saying, but the adoption of AI will not only change the technology your team is using but also how they operate together and with your technology stack.

The insurance industry includes numerous manual tasks that can be automated with AI and machine learning. With the advances in AI, insurance companies can provide faster services, ensuring customer satisfaction. As a result, the interest in AI insurance has tripled since 2012, according to Google Trends. Insurance providers can leverage a wide range of AI technologies like document processing, chatbots, and affective computing. They can implement these technologies in tasks, including claims and appeals processing, personalized insurance pricing, and fraud detection to achieve reduced costs, improved customer experience.

The ongoing adoption of AI and automation technologies will transform the way people work and cause a disruption, particularly in industries like real estate, finance and banking. Since the start of the industrial revolution, the world has seen skills shift in a way that has resulted in ever-changing jobs and newer skills required to keep pace with emerging technologies. According to McKinsey, these technologies "will bring numerous benefits in the form of higher productivity, GDP growth, improved corporate performance, and new prosperity, but they will also change the skills required of human workers." The real estate sector is in a great position to leverage AI and automation technologies to increase productivity, reduce costs and minimize errors. The number of workers who are engaged in manual tasks that only require basic cognitive skills will likely decline.

As the amount of data grows, AI could be used to classify and store documents and even proactively alert when a new appraisal is due or a property explodes in popularity, for example. Machine-learning enabled search could help people quickly analyze the massive amount of search data that exists by pre-processing and tagging useful meta-data for all property-related documents in a company's repository. How can companies keep up? According to the Altus Group report, two of the biggest challenges facing firms in collecting or utilizing more data to drive decision-making are a lack of internal capability and lack of appetite from the company to invest in the required technology. To solve for these challenges, consider a PwC report's digital transformation strategies for real estate organizations, which include these four steps:

We see the AI space poised for an acceleration in adoption, driven by more sophisticated AI models being put in production, specialized hardware that increases AI's capacity to provide quicker results based on larger datasets, simplified tools that democratize access to the entire AI stack, small tools that enables AI on nearly any device, and cloud access to AI tools that allow access to AI resources from anywhere. Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required. And AI processes have unique capabilities that can address an increasingly diverse array of automation tasks, tasks that defy what traditional procedural logic and programming can handle--for example: image recognition, summarization, labeling, complex monitoring, and response. Get a free trial today and find answers on the fly, or master something new and useful. In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products--and a majority of companies are starting to adopt machine learning.

We see the AI space poised for an acceleration in adoption, driven by more sophisticated AI models being put in production, specialized hardware that increases AI's capacity to provide quicker results based on larger datasets, simplified tools that democratize access to the entire AI stack, small tools that enables AI on nearly any device, and cloud access to AI tools that allow access to AI resources from anywhere. Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required. And AI processes have unique capabilities that can address an increasingly diverse array of automation tasks, tasks that defy what traditional procedural logic and programming can handle--for example: image recognition, summarization, labeling, complex monitoring, and response. Get a free trial today and find answers on the fly, or master something new and useful. In fact, in our 2019 surveys, more than half of the respondents said AI (deep learning, specifically) will be part of their future projects and products--and a majority of companies are starting to adopt machine learning.

Artificial intelligence has no doubt had a huge impact on business and society as a whole. As 2019 comes to a close, let's take a look at the new developments in automation, hardware, tools, model development, and more that will shape (or accelerate) AI in 2020. Signs point toward an acceleration of AI adoption. We see the AI space poised for an acceleration in adoption, driven by more sophisticated AI models being put in production, specialized hardware that increases AI's capacity to provide quicker results based on larger datasets, simplified tools that democratize access to the entire AI stack, small tools that enables AI on nearly any device, and cloud access to AI tools that allow access to AI resources from anywhere. Integrating data from many sources, complex business and logic challenges, and competitive incentives to make data more useful all combine to elevate AI and automation technologies from optional to required.