Adding artificial intelligence (AI) to the business world can introduce a lot of stumbling blocks.
AI can be used to retool processes or restructure the items that a company delivers. While Gartner has noted that AI is becoming more affordable for companies to implement and scale, the potential for sunk costs if something goes wrong keeps some companies from making the leap into AI adoption.
Other businesses, on the other hand, are eager to overcome AI’s friction if it means gaining an advantage. According to a KPMG report that examined the level of AI deployment across five industries. In all of these industries, there was a consistent theme indicating that, while they felt like they were advancing aggressively, they weren’t going quickly enough.
While AI is frequently linked with experimentation, a number of business leaders are beginning to see actual benefits from its use. Let’s examine the top industries effectively incorporating AI into their business models – and what you can learn from them.
The Current State of AI Adoption
In 2018, Gartner polled CIOs to see when they thought AI their businesses would start using AI. More than 60 percent of respondents said their companies would be using AI in production by 2020.
However, less than half of CIOs had accomplished this objective this by 2020. Growth had slowed but it had not stopped. And by now, probably one in three organizations is using AI in production. That is what’s propelling AI forward at a breakneck pace.
Let’s take a look at some AI statistics:
- By 2023, AI-powered voice assistants will number 8 billion.
- The global AI market is expected to be reach almost $60 billion by 2025. In 2016, the market was only worth $1.4 billion.
- By 2025, 50 percent of enterprises implementing AI orchestration platforms will use open-source technologies, alongside proprietary vendor offerings, to deliver state-of-the-art AI capabilities.
- 70 percent of organizations say developing and integrating AI techniques in applications is
a top priority.
- By 2025, 50 percent of enterprises will have devised AI orchestration platforms to operationalize AI. This shift is up from fewer than 10 percent in 2020.
- By 2025, 10 percent of governments will use a synthetic population with realistic behavior patterns to train AI while avoiding privacy and security concerns.
- By 2024, 60 percent of AI providers will include a means to mitigate possible harm as part of their technologies.
5 Industries Leading the AI Charge
Companies that use AI are motivated by three factors: the ability to cut expenses, develop faster, and grow profitably.
However, each industry’s approach to AI applications, as well as its problems and outcomes, may differ. Let’s take a look at a few industry-specific approaches to AI implementation:
1. Technology – Although the tech industry is the most advanced in terms of AI use and proof of concept, the KPMG report found that 73 percent of respondents believe their organizations should be more proactive in their AI investment and implementation. Decision-makers in the tech sector also agree that all organizations, regardless of industry, should have an AI ethics policy, and that government AI regulation is necessary. According to the report, machine learning, cognitive computing, and robotics are the AI technologies that will have the largest influence in the next two years. To embrace digitization, tech organizations must be daring, but they must also spend extensively in talent.
2. Retail – The financial benefits of AI programs at companies like Target and Walmart generated a significant financial edge for early adopters over laggards. If the rest of the industry does not implement machine learning and AI by 2025, they may find themselves at an unsurmountable disadvantage. The task ahead for retail is to take the AI technology it presently employs to enhance customer service and use it inside to identify efficiency. Retail was a very early adopter that kept AI siloed within the marketing organization. The industry has been using AI for client segmentation, targeting, and customer attrition for than a decade. Now, it’s up to retailers to employ AI to improve middle and back office tasks, such as financial forecasting and supply chain management.
3. Healthcare – With patient care as its central focus, healthcare is positively benefitting from AI in a variety of ways. According to a separate research from UnitedHealth Group, half of healthcare companies anticipate financial gains from technology like machine learning and deep learning, with a three-year return on investment. Keep in mind, though, that in a highly regulated field like healthcare, access to the necessary data sets – the backbones of successful AI implementation — can slow the pace at which enterprises may experiment with the technology. Like the financial services industry, healthcare has been reluctant to shift its systems to the cloud, which adds to the difficulty of implementing AI.
4. Transportation – The influence of AI on the transportation industry is anticipated to be significant. However, its influence might be interpreted in a variety of ways. AI will help nine out of ten industry leaders (92 percent) increase efficiency in their businesses, a larger expectation than in any other industry. However, decision-makers in the transportation sector are aware of the dangers: According to the KPMG report, 77 percent believe AI-driven products and services directly affect customer data security or privacy. Autonomous vehicles and the transformational influence they are predicted to have on how cities operate are driving transportation’s interest in AI. Because of this nexus between technology and public life, 82 percent of industry leaders believe the government should be involved in AI legislation “to some level.” Further, interest in AI’s ethical layer is a cross-industry phenomenon.
5. Finance – The financial services industry is experiencing a dramatically altered market where non-traditional institutions are drawing greater client interest thanks to a shift in consumer demand. AI will lessen the regulatory load on businesses in this new environment, allowing them to focus on the customer experience. Though financial services sectors rely on AI systems for product portfolio management and client segmentation, the industry is being urged to develop AI to reduce the amount of time and resources spent on regulatory compliance.
Stefanini is Your Partner for AI Adoption
It’s obvious that AI can help with the personalization that today’s corporate learning programs need. However, if your company is just getting started on this path, it might be difficult to know where to begin.
With our SAI suite, Stefanini has been developing a number of AI solutions for over 20 years. We have the necessary technologies and people in place to help you achieve your AI-enhanced R&D goals, with capabilities in intelligent automation, machine learning, natural language processing, and more.