Six steps to AI success has been saved
Six steps to AI success
Kick off a successful artificial intelligence (AI) initiative
Learn from early adopters of AI who are achieving positive results and learning from their experiences.
June 18, 2019
A blog post by Nitin Mittal, principal, Deloitte Consulting LLP and Dave Kuder, principal, Deloitte Consulting LLP.
Lessons learned from early adopters
Is your business among the 88 percent of organizations who say they are planning to increase spending on AI in the coming year?1 If so, you may be wondering where to get started and how to maximize the value of your investment. In our second State of AI in the Enterprise survey of 1,100 US business executives, we talked to early adopters who are achieving positive results and learning from their experiences. Though they face challenges, many of the companies we surveyed are successfully integrating AI across their operations—while earning economic benefits and creating long-term value.
Here are six considerations we gathered from their experience that can help you achieve AI success:
- Follow the rules for good implementation. Despite its complexity and transformational potential, implementing AI should follow the same best practices as any other technology. Companies should focus on project management and change management. Leaders of AI initiatives need to make sure that costs and impacts are tracked carefully, and results are reflected accurately. This "proof" will help fuel additional investment in AI projects.
- Address cybersecurity risks. Building cybersecurity into AI projects helps address the top risk cited by executives in the survey: They fear that the algorithms that deliver insights and the data that fuels those algorithms are vulnerable to attack. While no cybersecurity efforts can prevent every attack, incorporating security into the beginning of the process and making it a higher priority provides protection. Advances are being made to reduce risks associated with AI—for instance, forensic technology is getting better at detecting manipulated images and videos.2 Deep-learning models will likely also improve, helping companies to avoid regulatory noncompliance and other risks associated with bias in algorithms.
- Apply AI beyond the IT function. The top three AI use cases—IT automation, quality control, and cybersecurity—are largely focused on IT. While it makes sense that IT would be the first to roll out new technologies, AI's transformative potential is best realized when it enables change throughout the enterprise. Cloud can help achieve those objectives by providing users with easy access to AI-based capabilities.
- Take advantage of off-the-shelf solutions. Enterprise software and cloud services give companies options for adopting cognitive, without having to build everything from scratch. Cloud-based customer relationship management (CRM) and enterprise resource planning (ERP) software with cognitive capabilities that keep up with the latest improvements are widely available, as are chatbots. Many big cloud providers are developing subscription-based AI services aimed at specific business functions, such as product design and sales and marketing.3
- Prepare your workforce. Most organizations are still building a bench with strong AI capabilities. Trying to attract and retain AI talent may not be the best strategy, especially for companies just starting out. Using off-the-shelf solutions and cloud platforms are a good way to test the waters, while partners and consultants can also provide expertise and guidance. Long term, companies need to develop strategies for developing or adding talent to their IT team. While technical skills are essential, it's also important to have executives who understand the value of AI and can speak the language of technologists and programmers.
- Know where to automate, where to augment. Companies that automate simply to cut costs or improve efficiency are not taking full advantage of AI. Sure, there are clear use cases where automation is more efficient than humans. In other situations, machines will augment human decision-making by surfacing information, making predictions, and offering alternatives. Humans, by adding judgment, empathy, and business skill, will be able to apply this insight to make better decisions.
Come on in, the water's fine
It's clear that companies are becoming more sophisticated in their use of AI technologies and more companies are taking the plunge. Off-the-shelf tools are helping to make AI more accessible, while cloud-based solutions make it easier to explore AI's potential with minimal upfront investment and less need for in-house expertise. Is now the time for your company to take the leap and discover the value that AI-powered capabilities can deliver? Learn more from the experiences of early adopters or contact us.
1 Deloitte State of AI in the Enterprise, second edition.
2 Steven Melendez, "Can new forensic tech win war on AI-generated fake images?," Fast Company, April 4, 2018.
3 Ravi Akella, "What generative design is and why it’s the future of manufacturing," New Equipment Digest, March 16, 2018.
A webinar series on data science, artificial intelligence, and design thinking
Catch up on the latest