IBM Research Points to Global AI Growth in Businesses
IBM has commissioned new research into businesses adopting artificial intelligence (AI). It found that almost one-third of IT professionals surveyed globally say their business is now using AI, with 43% reporting that their company has accelerated their rollout of AI as a result of the COVID-19 pandemic.
AI is changing the way businesses operate in fundamental ways, from how they communicate with their customers through virtual assistants, to automating key workflows and even managing network security. Recent advances in technology are making AI more accessible than ever, but the annual survey also found that a lack of AI skills and increasing data complexity are cited as top challenges.
The survey determined the top three barriers to AI adoption for businesses are: Limited AI expertise or knowledge (39%), increasing data complexity and data silos (32%), and lack of tools/platforms for developing AI models (28%).
Key findings from the Global AI Adoption Index 2021
- Business adoption of AI was basically flat, but significant investments in AI are planned: Almost one-third of companies reported using AI in their business, similar to 2020 findings. For those deploying or exploring AI, they report it is being driven by multiple pressures and opportunities businesses are facing, from the COVID-19 pandemic to advances in the technology that make it more accessible. A third of global IT professionals report their company plans to invest in both skills and AI solutions over the next 12 months.
- COVID-19 accelerated how businesses are using automation today: 80% of companies are already using automation software or plan to use this technology in the next 12 months, and for more than one-in-three organisations, the pandemic influenced their decision to use automation to bolster the productivity of employees, while others found new applications of this technology to make themselves more resilient, such as helping to automate the resolution of IT incidents.
- Trustworthy and explainable AI is critical to business: 91% of businesses using AI say their ability to explain how it arrived at a decision is critical. While global businesses are now acutely aware of the importance of having trustworthy AI, more than half of companies cite significant barriers in getting there including lack of skills, inflexible governance tools, biased data, and more.
- The ability to access data anywhere is key for increasing AI adoption: The proliferation of data across the enterprise has resulted in over two thirds of global IT professionals drawing from more than 20 different data sources to inform their AI. Almost 90% of IT pros say being able to run their AI projects wherever the data resides is key to the technology's adoption.
- Natural language processing is at the forefront of recent adoption: Almost half of businesses today are now using applications powered by natural language processing (NLP), and one-in-four businesses plan to begin using NLP technology over the next 12 months. Customer service is the top NLP use case with 52% of global IT professionals reporting that their company is using or considering using NLP solutions to improve customer experience and it was the use AI case IT professionals were most likely to report that the COVID-19 pandemic has increased their focus on.
"As organisations move to a post-pandemic world, data from the Global AI Adoption Index 2021 underscores a major uptick in AI investment," said Rob Thomas, Senior Vice President, IBM Cloud and Data Platform. "A large majority of those investments continue to be focused on the three key capabilities that define AI for business - automating IT and processes, building trust in AI outcomes, and understanding the language of business. We believe these investments will continue to accelerate rapidly as customers look for new, innovative ways to drive their digital transformations by taking advantage of hybrid cloud and AI."
The advantages and disadvantages of AI in cloud computing
Cloud computing offers businesses more flexibility, agility, and cost savings by hosting data and applications in the cloud. AI capabilities are now combining with cloud computing and helping companies manage their data, look for patterns and insights in information, deliver customer experiences, and optimise workflows.
We take a look at some of the benefits and drawbacks of AI in cloud computing.
The benefits of AI in cloud computing
A major advantage of cloud computing is that it eliminates costs related to on-site data centers, such as hardware and maintenance. Those upfront costs can be restrictive with AI projects, but with cloud enterprises you can access these tools for a monthly fee, making research and development related costs more manageable. AI tools can also gain insights from the data and analyse it without human intervention, reducing staff costs.
AI is able to identify patterns and trends in large data sets. Using historical data, AI compares it to the most recent data, which provides IT teams with well-informed, data-backed intelligence. AI tools can also perform data analysis fast so enterprises can rapidly and efficiently address customer queries and issues. The observations and valuable advice gained from AI capabilities result in quicker and more accurate results.
Improved data management
AI enables extensive data management, and cloud computing maximises information security, making it possible to deal with massive amounts of data in a programmed manner to analyse them properly, allowing the business to leverage information that has been “mined” and filtered to meet each need. AI can also be used to transfer data between on-premises and cloud environments.
Businesses use AI-driven cloud computing to be more efficient and insight-driven. AI can automate repetitive tasks to boost productivity, and also perform data analysis without any human intervention. IT teams can also use AI to manage and monitor core workflows. IT teams can focus more on strategic operations while AI performs the mundane tasks.
With businesses deploying more applications in the cloud, security is crucial in order to keep data safe. IT teams can use different AI-powered network security tools which can track network traffic, they can flag issues, such as finding an anomaly.
The drawbacks of AI in cloud computing
Enterprises need to create privacy policies and secure all data when using AI in cloud computing. AI applications require a large amount of data, which can include consumer and vendor information. While some data can be anonymous and can't be tied to personally identifiable information, knowing who the data belongs to makes it more valuable. When sensitive information is used, data protection and compliance is a major concern.
IT teams use the internet to send raw data to the cloud service and recover processed data. Poor internet access can hinder the advantages of cloud-based machine learning algorithms, as cloud-based machine learning systems need consistent internet connectivity.
While processing data in the cloud is quicker than conventional computing, there is a time lag between transmitting data to the cloud and receiving responses. This is a significant issue when using machine learning algorithms for cloud servers, where prediction speed is one of the primary concerns.