AI and the human experience: A balance of scale and skill Bookmark has been added
AI and the human experience: A balance of scale and skill
The challenges and opportunities from advancing technologies
Alan Schulman discusses the importance of blending digital utility at scale with human centered design and narrative skill.
- Developing great digital experiences
- Advancements from artificial intelligence and machine learning
- Creating the right balance between scale and skill
- Get in touch
- Related topics
Developing great digital experiences
Marketers know that strong narrative content can be an essential part of delivering great digital experiences—as fundamental as hooking a customer with an inspiring advertising story. But in an age when human interaction with digital devices has become like a sixth sense, more than ever before, marketers should consider developing experiences that balance both digital utility at scale with human-centered design and narrative skill.
It’s easy to imagine the potential of what artificial intelligence (AI) and machine learning applied to content can generate at scale, especially in an always-on world when today’s global marketers often need to produce more content with less budget. But the real potential for AI and machine learning may be the multiplier effect that can occur when you combine the efficiencies it delivers in content authoring and production with the time savings it returns to allow the human craft skills of content ideation and creation to focus on what they do best—intrigue, involve, and ultimately persuade customers to act.
Advancements from artificial intelligence and machine learning
New research has revealed how recent advances in artificial intelligence and machine learning are now capable of delivering both greater insights, automated narratives, and greater efficiencies in digital production and delivery. In Deloitte’s latest CMO Survey report, a majority of respondents anticipate using AI for some level of content personalization (56 percent), and predictive analytics for customer insights (56 percent) over the next three years. Meanwhile, significant percentages of respondents foresee applying AI to customer segmentation (40 percent), programmatic advertising and media buying (38 percent), and improving marketing ROI by optimizing marketing content and timing (33 percent).
As AI accelerates, it can help significantly scale the long tail of digital content production—making customization, adaptation, and multiple language versioning much more efficient for marketers and their agencies. But what may be even more exciting to ponder are the more salient and near real-time insights that predictive AI can provide skilled content creators to help guide what content will be most relevant. New entrants such as the AI firm Persado use natural language generation that learns in parallel with client marketing campaigns in near real-time to determine which messages perform best—adding efficiency through AI and boosting effectiveness on the content side. Streaming media services such as Spotify are already leveraging machine learning to tailor playlists down to titles, artists, and musical styles to provide real personalization to add value to subscriptions and enhance the human listening experience.
At Deloitte, we’re leveraging our own brand of predictive AI with an engine called Blab that analyzes thousands of online conversations and predicts those that will be trending from the next 24 to 72 hours out. By getting a view of where the cultural conversations are moving, our clients are able to better understand when there are conversations they can organically align to, which allows the skills of our content creators to create meaningful, relevant opportunities to join those discussions and amplify client brand purpose—even drive sales activations.
There’s clear momentum for AI and machine learning to have an impact beyond marketing in other dimensions such as new product and service development as well. In The CMO Survey, B2C product companies rank highest on the use of AI for everything from customer segmentation to autonomous objects. Innovations in AI and machine learning are also spanning the creative to production process through software that generates designs for consumer goods such as furniture, based on customers’ preferences for size, material, and overall feel.
But even as AI and machine learning technologies improve both efficiency and effectiveness, creating the right balance between digital transformation and human experience, between scale and skill, becomes key.
Balancing the human experience with artificial intelligence
Creating the right balance between scale and skill
After all, algorithms don’t feel, humans do. To date, what we have seen as attempts to automate brand’s way into the customer’s heart are missing the mark—such as a recent advertisement for an open job position generated by AI featuring awkward and incomplete sentences. By putting the efficiency of scale at the wheel of content creation, storytelling, and customer engagement, the best of intentions can likely unravel.
Despite broad adoption of AI and machine learning, these technologies aren’t quite suited to take over the entire content supply chain—particularly all levels of customer or employee engagement, for that matter. But leveraging AI to help the process of informing, testing, producing, implementing, and optimizing content, can lead to breakthroughs with very human results.
The challenge of creating content that intrigues and involves is still very much a human skill process. While the scale that predictive AI and machine learning enables holds enormous possibilities to make both the front and long tail of digital marketing more insightful and efficient. The good news is, if you find the right the balance between both digitization and the human experience, you don’t need to sacrifice skill for scale on your path to growth.