Accenture's Technology Vision 2018 report tackles this question by highlighting trends and rapid advancements in technologies that are improving the way people work and live. The report highlights a need for a fundamental shift in leadership that is required to cultivate partnerships with customers and business partners, and to further accelerate the adoption of artificial intelligence as the fuel for enterprises to grow and deliver social impact.
Accenture's 2018 report, called Intelligent Enterprise Unleashed: Redefine Your Company Based on the Company You Keep, highlights how rapid advancements in technologies -- including artificial intelligence (AI), advanced analytics and the cloud -- are enabling companies to not just create innovative products and services, but change the way people work and live. This, in turn, is changing companies' relationships with their customers and business partners.
"Technology," said Paul Daugherty, Accenture's chief technology and innovation officer, "is now firmly embedded throughout our everyday lives and is reshaping large parts of society. This requires a new type of relationship, built on trust and the sharing of large amounts of personal information."
Accenture identifies five emerging technology trends that companies must address if they are to build the partnerships needed to succeed in today's digital economy:
1. Citizen AI: Raising AI to Benefit Business and Society. As artificial intelligence (AI) grows in its capabilities, so does its impact on people's lives. Businesses looking to capitalize on AI's potential must acknowledge this impact, "raising" AI to act as responsible representatives of their business.
"72 percent of executives report that their organizations seek to gain customer trust and confidence by being transparent in their AI-based decisions and actions." -- Accenture
2. Extended Reality: The End of Distance. Virtual and augmented reality technologies are transforming the ways people live and work by removing the distance to people, information and experiences.
"27 percent of executives state it is very important for their organization to be a pioneer in extended reality (XR) solutions." -- Accenture
3. Data Veracity: The Importance of Trust. By transforming themselves to run on data, businesses now face a new kind of vulnerability: Inaccurate, manipulated, and biased data that leads to corrupted business insights and skewed decisions. To address this challenge, companies must follow a dual mandate to maximize veracity and minimize incentives for data manipulation. "The presence of bad data in a system isn't always the result of malicious intent, but may be a sign that a process isn't working the way it was intended," said Accenture.
"84 percent of executives agree that through technology, companies are weaving themselves seamlessly into the fabric of how people live together." -- Accenture
4. Frictionless Business: Built to Partner at Scale. Businesses depend on technology-based partnerships for growth, but their own legacy systems aren't designed to support partnerships at scale. To fully power the connected Intelligent Enterprise, companies must first re-design themselves.
"60 percent of executives acknowledge that blockchain will be critical to their organization over the next three years." -- Accenture
5. Internet of Thinking: Creating Intelligent Distributed Systems. Businesses are making big bets on intelligent environments via robotics, AI and immersive experiences, but bringing these intelligent environments to life will require not only adding key skills and workforce capabilities, but also modernizing current enterprise technology infrastructures.
"63 percent of executives believe it will be critical over the next two years to leverage customer hardware and hardware accelerators to meet the computing demands of intelligent environments." -- Accenture
The Accenture Technology Vision report is very robust. The focus of this article is on the Citizen AI trend. Before we dive into the artificial intelligence (AI) portion of the report, here is a glossary of useful AI terms:
Citizen AI: Raising AI to Benefit Business and Society
According to Accenture's Technology Vision report, deploying AI is no longer just about training it to perform a given task. Successful deployment of AI systems is about "raising" it to act as a responsible representative of the business and a contributing member of society. Accenture suggests that "as AI systems learn, make autonomous decisions, they have grown from a tool to a partner, coordinating and collaborating with people at work and at home."
Accenture highlights examples of AI systems in healthcare, retail, insurance, and the tech industries where AI is much more than just a tool. AI is now a public face of businesses, interacting directly with customers via chat, voice, and email in a customer service capacity. In 2017, Accenture said AI is the new UI and that AI is about to become your company's digital spokesperson. AI systems today are now actively driving sales forecast meetings.
"Global corporate spending on cognitive / AI systems will increase at a 54 percent compound annual growth rate (CAGR) between 2015 and 2020." -- IDC
As of February 2018, there are 2,117 AI startups, segmented into 13 categories that collectively raised $29 billion in funding, according to Venture Scanner.
Accenture advises business leaders that along with the new responsibility of "raising" AI, companies create portfolios of AI systems with varied skills. Raised AIs can scale operations, adapt to new needs via feedback loops, and create collaborative new members of the workforce.
Businesses today must view AI as systems that can learn instead of systems that are programmed. The pace of deep neural network innovation means companies can now solve an entirely new set of problems. Learning based AIs can develop overtime to collaborators and new members of the workforce. Virtual Personal Assistants (VPAs) is an example of how augmented insights from AI powered applications improve decision based activities.
Business leaders must understand wrong and right, behaving responsibly, imparting knowledge without bias, building self-reliance and at the same time promoting collaboration and transparent communication. The value and outcomes that are guided by learning-based AI systems are functions of the data volume and quality. These systems use data to build models that overtime become more accurate and precise.
"To meet this new responsibility of raising AI, companies can look to milestones of human development for guidance: first, people learn how to learn, then they rationalize or explain their thoughts and actions, and eventually they accept responsibility for their decisions." -- Accenture
With successfully trained and raised AI, a company essentially creates a new worker. This new worker will add incredible value if the best data is available to train it. The better the data, the better the AI system. Accenture's report highlighted Google's use of 65,000 clips of words being spoken in order for their AI system to understand just 30 words in a single language. The scale of training data has helped Google's voice recognition to reach 95-percent accuracy. A good example of this new AI worker will be chatbots that directly engage with customers as your company's new customer service reps.
The report suggests that businesses must use care when selecting taxonomies and training data in order to minimize biases in the data. Research from University of Virginia discovered that AI amplifies predictable gender biases found in photos -- for example, men standing next to a stove were categorized as women.
The ability to explain the process used to arrive at a decision is a critical need in business. Companies must build AI systems that provide clear explanation of their guidance and recommended actions. In the finance industry, AI systems are used to review credit card applicants, and in order to reject applicants, companies must provide explanations to customers per banking regulations. In addition, government policymakers will develop rules to govern decision-making aspects of AI systems. An example is the European Union's General Data Protection Regulations (GDPR) that gives individuals a "right to explanation" for decisions sourced from AI algorithms.
"88 percent of executives state it is important for employees and customers to understand the general principles used to make AI-based decisions by their organization." -- Accenture
My company uses AI-powered powered CRM to analyze customer service, sales, and marketing insights using machine learning algorithms. When a marketing lead or a sales opportunity is scored by AI, the system provides the exact parameters used to derive the score. It is critically important for AI systems to deliver algorithm transparency to end-users in order to immediately establish trust.
AI systems must be responsible. The AI system represents the company's brand and its core values and guiding principles. Businesses must fully understand their liability as it pertains to AI-systems collaborating with employees (like smart robots in factories) or autonomously (like financial trading or wealth management advisory). Accenture uses Audi as an example, where the company will assume liability for accidents involving its 2019 A8 model when its AI system is in use.
Businesses cannot hesitate to raise AI systems or they will fall behind regulations, public demand, and strict regulatory controls placed on them. Digital savvy business leaders will create a responsible, explainable AI system. In a hyper-connected, knowledge-sharing economy, where customers and employees are connected more than ever before, companies that invest in raising AI systems that can collaborate with people in a transparent and trustworthy manner will create a sustainable growth strategy.
"72 percent of executives report that their organization seeks to gain customer trust and confidence by being transparent in their AI-based decisions and actions. This will be a crucial step in integration of AI into society. Call it "Citizen AI". -- Accenture
Fast forward to 2020, and I believe that sales, marketing, and customer service without AI is no longer effective or acceptable sales, marketing, or customer service. We are in the age of the connected stakeholder -- customers, business partners, employees, and communities. Every business, large and small, must transform to an AI-driven business. Companies and workers are less likely to be replaced by robots and more likely to be disrupted by companies and workers that are trained to use AI technologies to compete and win.
In a digital economy, where the battleground is clearly defined by customer experience, the new business currencies that matter most are trust, intelligence, speed, personalization, and scale. The agile and digitally transformed enterprise of tomorrow is powered by AI, levering augmented insights to rapidly co-create value, and deliver meaningful results.