5 Ways to Make AI Work for Your Organization

Artifical Intelligence is a divisive topic, with both advocates and skeptics dominating the headlines. Elon Musk and Stephen Hawking have warned about AI’s destructive potential, while others have more grounded concerns relating to automation and jobs. Hysteria and hyperbole tend to surround anything new, but CEOs and organizational leaders across industries have the opportunity to take a levelheaded approach to AI and its potential.

The technology is somewhat nascent. Although the future remains hazy, investing in education is the smart play. Companies need to better understand AI’s potential if their leaders hope to stay ahead of the game. Here are five ways you can apply a similarly measured approach and ensure your organizaton is well-positioned for the future.

1. Invest in AI-related research and innovation.

The AI field has grown by leaps and bounds in recent years, but its real tangibility remains unclear. Still, this shouldn’t deter companies from forging ahead and finding approriate uses for AI. Indeed, gaining a first-mover advantage can be worth the cost of investing in research and development.

According to the McKinsey Global Institute, technology mainstays such as Google and Baidu invested between $20 and $30 billion in AI during 2016, with 90 percent of those figures channeled directly into R&D. Startups also saw the signs, devoting $6 to $9 billion to AI research. More important, at least 20 percent of AI-aware firms reported themselves as early adopters.

AI has made a significant difference in several clear-cut use cases. Motorcycle manufacturer Harley Davidson improved lead generation by 2,930 percent in the three months after it implemented an AI-based marketing system named Albert. Other companies are showing strong results for AI and machine learning — particularly when it comes to generating actionable business insights and boosting sales.

Nearly 80 percent of companies incorporating AI solutions have benefited from better insights and analysis, according to Capgemini’s State of AI Survey for 2017. AI also enabled JP Morgan’s legal team, which reportedly spends hundreds of thousands of hours studying deals, to analyze thousands of documents in seconds while significantly reducing errors.

Research’s goal is finding applicable-use cases, then adapting AI technology to serve the company’s need. Implementing AI for adoption’s sake never should be the norm. That route rarely leads to true operational improvements.

2. Use AI as intended: to complement, not replace.

One of the largest fears surrounding AI is that the technology will depreciate the value of human capital. The argument follows this logic: AI leads to automation and reduces the need for costly human labor because machines can perform the same functions with higher efficiency and less expense.

While compelling, this argument is somewhat flawed. The same Capgemini study found the majority of companies surveyed saw increases in job opportunities alongside improved efficiency and service. Understanding how AI can complement a company’s operations is far more productive than worrying about how it will destroy the labor force.

Moreover, most AI technologies still are limited relative to human capability in several areas. For best results, companies should create systems that highlight the strengths of each. KLM, for example, implemented an AI-assisted customer-service model. The system uses AI to interpret inquiries through the company’s communication channels and offer potential responses to agents, cutting down wait times and improving passengers’ overall satisfaction.

Others, such as China Merchants Bank, have replaced front-line support with AI-enabled chatbots that can resolve most basic queries. This gives support staff greater time to focus on customers with bigger, more complex problems. The lesson learned? Adapt AI technologies to fit areas of real need and find sectors in which technology can help people do their jobs better. In the process, companies effectively will streamline operations.

3. Educate yourself and your team.

Innovation and new technology always come with a knowledge gap. While early adopters are learning, the mainstream tends to be several steps behind. A joint survey from BCG and MIT’s Sloan Management Review found that leaders in most industries believe AI technology will have a significant impact during the next five years. Companies are beginning to realize the potential for AI-based platforms and the ever-increasing need to be informed. BCG and Sloan reported that 83 percent of respondents viewed AI as a strategic opportunity for expansion.

For most, developing a high-level technical knowledge of AI is not entirely necessary. What is critical, though, is understanding the technology enough to recognize its potential implications. Executives should be aware of AI essentials, such as how programs learn from data, how AI systems can be integrated into every-day operations and how investing in innovation could better position companies for future competition.

At the same time, leaders constantly should scrutinize their workforces to find areas in which AI implementation could improve operations and offer tangible gains. Employees should be trained and educated in AI via online courses, certifications and similar programs designed to help them prepare for the impending proliferation of AI technology.

4. Create new jobs to manage AI fields.

Some claim that engineers and other highly technical professions will be hit hardest by the evolving AI boom. However, expert studies and industry trends suggest otherwise. While technological revolutions may cause job losses in the beginning, these advances offer a long-term balance: new jobs and fields to handle the work.

To remain relevant, AI-aware firms should start shifting jobs and available opportunities toward a paradigm that complements the new technological direction. AI can replace many lower-level tasks required in day-to-day operations — data analysis and marketing among them — but these systems still will require monitoring and constant adaptation.

It’s crucial to create these jobs across companies and not solely in technology-related departments. System maintenance is vital, but understanding the application of AI systems is a broader question. It requires several departments to identify a relevant use case and ensure smooth adoption.

5. Keep the ‘human’ in HR.

AI is evolving and constantly finding new uses, and leaders always should strive for a sense of balance in how these strategies are implemented. Automation might seem favorable in all cases, but some fields require a less analytical, human touch. General Human Resources, for example, requires analytical skills but also the capacity to be emotionally available when responding to employees’ needs and concerns.

Though machines can handle one aspect of the HR job description, employees feel more comfortable and heard when another human is present. AI will remain valuable in areas such as payroll, recruitment, understanding employee efficiency and allocating labor. But AI never will fully replace your HR department. While focusing on analytics alone will result in unhappier employees, forward-thinking companies already are using AI to give their HR staff members tools to do their jobs better.

Despite the uncertainty surrounding the field, one thing is for certain: AI will keep expanding. Successful case studies and breakthroughs showcase the technology’s potential and sustainability. In the face of this new wave, companies are well-advised to continue creating, discovering and innovating to become forerunners in AI implementation.