FEATURED STORY OF THE WEEK
How AI Will Transform the World in the Next 30 Years
Today’s smart digital technologies have been critical to overcoming the early disruptions of the 2020s. Artificial intelligence (AI) is at the heart of this transformation, where 50% of companies had already adopted AI in at least one business function in 2020, McKinsey reports. Modern applications include manufacturing, customer service, human resources, and others, where any use case that requires intelligence and decisions has AI in place or on the horizon.
In fact, AI is at the cusp of its own transformation as Deep Learning becomes available to companies worldwide. In this article, we explore the future of AI—including its democratization, making its capabilities become available to everybody; and its real-time applications, so that it becomes and intrinsic part of our everyday lives.
What is “AI” as We Conceive IT Today?
It’s difficult to provide holistic definition of today’s artificial intelligence (AI), let alone define it in the context of future applications. We can describe today’s AI as being a product of the “Age of Statistical Learning,” as Forrester describes, where companies have begun “applying machine learning algorithms to… build predictive models and surface insights.”
Modern AI’s augmentation of human intelligence is a departure from the AI conceived decades ago, which sought to mimic human intelligence. As a result, today’s business applications most often involve connecting human beings to AI-driven solutions the improve decision making and optimize best practices. Networked technologies like 5G, augmented reality (AR) via mobile devices, and blockchain make AI-driven tools available to more people—including consumers—even if they lack a technical background themselves.
Current Market Drivers for AI Adoption
Although AI was critical to the success of firms who persisted during this decade’s initial disruptions, we also learned that initial applications weren’t as ready as they should have been in facing down those challenges (e.g. the COVID-19 pandemic). Now, business leaders face new pressures to expand AI capabilities to both their business users and their customers, where applicable.
As a result, 35% of “adaptive and growth-mode firms” are investing in workplace AI solutions to “help workers deal with disruption,” Forrester reports. Increasingly, AI must become part of “edge” functions of the business—whether that means aiding everyday workers with critical functions and decisions, or delivering better experiences for consumers as they access a chatbot or mobile app.
10 Use Cases for Future AI
Thanks to connected, cloud-native digital infrastructure that spans on-premise and remote environments, there are no limitations to the potential reach and impact of tomorrow’s AI applications. But what benefits and experiences will AI fuel beyond the business intelligence (BI) and automation use cases it’s most often used for today? Here we take a look at 10 future applications, most of which are already underway shaping our collective future.
1. Augmenting Creativity
Far from replacing human intelligence, the most successful use cases for AI involve augmentation of human intelligence through predictive analytics, natural language processing (NLP), and other capabilities. These types of AI already free up workers so they can focus on creativity. In time, AI will go even further to support human beings in their creative pursuits—AI will “help us to think differently,” as Forrester describes, where “The sea of data that AI can quickly process will produce unique insights that can spur new ideas.”
2. Supercharging Business Decisions
AI’s ability to augment human intelligence and empower human beings to make better decisions will become more sophisticated in other ways as well. More than only optimizing individual business decisions, AI will produce insights from across business units and functions through deep analysis, enabling teams from across departments to collaborate in ways not possible before.
In the complex field of insurance risk analysis, for example, AI will vastly improve how policies are priced based on financial risk. That’s because AI can quickly input and analyze data regarding any number of risk factors, many of which might not be visible to a single analyst tasked with one of dozens of assessments on a given day.
3. Enabling Explainability
One underappreciated barrier to AI adoption is the question of whether or not human beings trust its outcomes (e.g., predictions or recommendations those individuals don’t want to hear). Explainable AI (XAI), once a somewhat obscure discipline within the field, is receiving renewed attention because of its ability to “explain” the machine-learning models and their outcomes to non-technical humans. In this way, even everyday users who rely on AI for work or personal needs can access an explanation as to why their AI-based tools do what they do.
This is especially valuable at the C-Suite level, where deep technical knowledge may be lacking but critical decisions happen every day. Companies who perform well with AI are 2.3 times more likely than others to report a very effective C-Suite, McKinsey reports, where their robust capabilities contribute directly to high-level decision making at those companies. Explainable AI can customize explanations based on recipients as well, so that explainability is accessible to just about everyone.
4. Supporting Next-Generation Communications
As digital communications continue their transformation, AI will become the backbone of more sophisticated platforms and continue to enhance the way we connect with one another. In addition to supporting wondrous experiences such as holographic meetings or dynamic, real-time data visualizations, AI will improve how teams collaborate. Specifically, AI may analyze the skillsets of individual team members, align them in collaborative groups to meet certain objectives, and provide real-time recommendations and query-responses during digital communications to support those goals.
5. Democratizing Education
AI is already penetrating formal education, where AI in U.S. education has grown by 47.5% from 2017 to 2021, Research and Markets reports. But AI can do more to educate the world by breaking out of traditional barriers that make education inaccessible to disadvantaged populations. Instead, AI will use internet to connect and optimize educational resources based on individual needs. Conversational AI, which enables anyone to communicate with AI through common language, will ensure no matter the person’s base education, that person can achieve any level of education starting with simple speech.
6. Allowing for Smarter Forecasting
Forecasting is a critical technique in modern business that relies too often on “gut instinct.” This especially applies to B2B sales teams where often instinct and relationships are the best sales resources available. But prescriptive forecasting driven by AI can supplement those instincts, using insights from both structured data (e.g., quantitative market data) and unstructured data (e.g., conversations, direct messages) to help salespeople make better decisions. AI can align its recommendations with specific sales goals as well, ensuring its support is always contextually relevant to the sales teams it supports.
7. Delivering Business Intelligence to Everyone
The democratization of business intelligence (BI) is already underway, and AI can do more to make the advanced analytics of BI more accessible to everyday employees. Conversational AI, combined with contextual analysis of employee habits and workflows, will make AI a partner to employees at all levels of the organization. AI can deliver insights at opportune moments during employees’ daily work as employees “train” their individual instances of AI to work with them successfully.
8. Improving Closeness with Customers
Even today, customer service channels are notorious for being tedious and (ironically) unhelpful, with excessive wait times and associates who too often are unable to help. AI can optimize customer service processes through chatbots and augmentation of service interactions, often by providing service teams with AI resources during interactions with customers. AI can impact other key aspects of the customer experience (CX) as well, through hyper-personalization, automation, and adaptation based on individual customers’ preferences.
9. Transforming Transportation
AI will transform experiences of individual travelers through self-driving cars and even flying vehicles. But AI will transform the transportation sector even further through its macro-level applications. “Leveraging AI in transportation helps the sector increase passenger safety, reduce traffic congestion and accidents, lessen carbon emissions, and also minimize the overall financial expenses,” says Forbes. Predictive analyses using data from IoT sensors in individual vehicles can reduce maintenance and administration costs in the freight industry by 45% as well.
10. Helping Us Live Our Best Lives
In some straightforward ways, AI will improve the daily lives of those without substantial wealth for whom connected digital technology is nonetheless already ubiquitous and accessible. AI can improve our communication with loved ones, for example; it also can make more personalized recommendations about our individual health.
But AI will help the humanity in more universal and compassionate ways as well. AI will aid governments, nonprofits, and charity organizations work to overcome global crises like famine; AI also will aid us in improving conditions for the sick and disabled through personalized medicine.
The Truth About AI: is That It’s All About People
The original conception of AI—that it will someday replace human beings in vital capacities—has turned out to be dead wrong. The opposite is true: AI is enhancing how human beings do their work, live their personal lives, interact, educate, and aid one another in profound and transformative ways.
Companies’ success with AI depends on their people as well. There is a compound effect as more and more employees access AI successfully, where their own labor improves as well as their collaboration with others. That’s why most AI high performers (55%) have their own roadmap that connects AI with business value across their organizations, McKinsey reports.
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