Six ways to think about AI integration
In the world of technology and business, not a day goes by without the mention of artificial intelligence (AI) and its power to disrupt almost every industry imaginable.
Whether the phrase rubs you up the wrong way for its (often inaccurate) overuse, or the vast possibilities of the technology truly excite you, one thing seems certain; it’s here to stay.
According to a survey of 1,000 US businesses by PwC, 20 percent plan to implement AI technology across their enterprises in 2019. The result of this continual movement could see AI contribute up to US$15.7 trillion to the global economy by 2030.
If your company is tentatively weighing up how AI could bring value to the business, it’s worth starting with PwC’s six considerations for implementation and where the technology could play a fundamental role in 2019.
# 1 | Structure
‘Where ROI and momentum is paramount.’
In terms of structure, the emphasis should be on organizing the enterprise for Return on Investment (ROI) measures and momentum. Scaling up by moving AI models into production will ensure operations enhance decision-making and provide forward-looking intelligence. Businesses should set up a diverse team that has business, IT and specialized AI skills in an organizational structure that crosses functions, and be responsible for identifying use cases, and how to develop accountability and governance.
# 2 | Workforce
‘AI citizens and specialists need to work together.’
Upskilling is seen as a major challenge for most companies, with 31 percent of executives worried about the inability to meet the demand. Workplace culture is also seen as a big pull-factor for job seekers who crave organizational excellence, resources, definition of roles, exciting research and individual empowerment. Currently, the challenge is to fill jobs. Upskilling can create citizen users and developers, but you’ll likely need to hire highly-trained programmers and data scientists. Forming partnerships with colleges or apprenticeships is a suitable place to start.
# 3 | Trust
‘Making AI responsible in all its dimensions.’
Top executives believe that their top challenge for 2019 is to ensure that their AI systems are trustworthy. The key tenets of responsible AI revolve around fairness, interpretability, robustness and security, governance, and finally ethics. Some companies, such as Salesforce, are setting up ethics boards or chief ethics officers for technology. Job roles which combine technical expertise with an understanding of regulatory, ethical and reputational concerns can only be a good thing.
# 4 | Data
‘Locate and label to teach the machines.’
As far as data is concerned, the survey highlighted the top AI-related data priority for 2019 is to integrate analytics systems to gain business insights. For this to happen, data labeling must be of equal priority. Labeling data is crucial for machine learning to detect patterns in the present and predict the future. Meanwhile, emerging regulations around data privacy— such as GDPR and the California Consumer Privacy Act— are cited as additional considerations for how companies operating globally can use data generated across territories.
# 5 | Reinvention
‘Monetizing AI through personalization and higher quality.’
Now for the interesting part, reinvention. A recent Global Artificial Intelligence Study found that most of AI’s economic impact will come from the consumption side, as higher quality, more personalized and data-driven product and services come from vertical markets such as healthcare, retail and automotive.
AI in healthcare, for example, could enable new business models based on monitoring patient lifestyle data; quicker and more accurate diagnoses of cancer and other diseases; and personalized and adaptive health insurance. Retailers are already using AI to anticipate trends and guide the business to meet them. Next up is hyper-personalized retail: AI and automation make it feasible for retailers to offer a growing number of products or services made specifically for one individual.
# 6 | Convergence
‘Combine AI with analytics and the IoT.’
Lastly, the true magic is occurring in the area of convergence. PwC highlights the essential eight technologies as AI, augmented reality, blockchain, drones, IoT, robotics, virtual reality, and 3D printing. As AI will help advance predictive and streaming analytics, the convergence makes new data-driven business models more powerful. Embodied AI, which could be embedded in AI chipsets that are directly within IoT devices can create local intelligence as well.
Ultimately, as 2019 beckons, every company considering AI implementation should establish a strategy with their own distinctive organizational structure and workforce plans, trustworthy algorithms based on the right data and a dedication towards reinvention— converging existing and emerging technologies— with the ultimate aim of growing revenue and profit.