How can you best connect and engage with human beings? The answer is simple. Keep individual aspirations and personal values at the center of innovation and interaction. It is the hardest part of many technical, operational, and commercial processes supporting product and content leadership. Digital enablement, transformation, and acceleration must understand human life and its diverse facets in order to thrive.
Assuming that artificial intelligence (AI) is meant to be augmented or enriched intelligence rather than mere automation, cultural intelligence has to be part of anticipation, definition, and execution. Identifying and implementing the right level of cultural effectiveness is vital to delivering compelling products and services how, when, and where it matters most. Equally important as linguistic and functional effectiveness, cultural effectiveness is deeply rooted in customer journeys and experiences from the outset. Moreover, cultural intelligence is as sensitive as it is challenging when you are aware of all layers of underlying standards, unspoken norms, and generated reactions that have to be addressed simultaneously and well-balanced with other business-critical factors such as speed and cost.
There is no way to standardize cultural intelligence and no silver bullet to enforce it since it varies according to targeted environments, content, products, and audiences more often than not. Yet some general recommendations should be kept in mind if you are involved in any stage of product or content lifecycles. Cultural intelligence should be understood here as data-driven knowledge, soft competencies, and business processes empowering you to develop capabilities to embrace local customer cultures and interact, collaborate, convince, and deliver across culturally shaped markets. Leveraging cultural intelligence at scale puts you in the best position to deploy AI at large. And doing so adds value to AI by extending and increasing its performance including tasks that are less basic or repetitive and request more cognitive power. Here is some advice:
Tie Cultural Intelligence to Business Objectives
It’s important to ensure cultural intelligence is tied to business objectives in a tangible and measurable way. It may be viewed as an abstract concept, or a no danger zone if it is not formally integrated in roadmaps and plans of records. Cultural intelligence conveys all elements and arguments creating motion and emotion among local customers.
You should definitely understand and bear in mind what makes your products and services authentic and immersive, long before they are purchased. At the end of the day, cultural intelligence makes content (more) different, intuitive, and actionable over time. If you embed such factors in AI-driven processes as profit drivers, rather than international dependencies, in your strategy, you can define criteria and indicators measuring cost and time effectiveness correlated with (or without) commercial success.
On the one hand, you need to use the right mix of cultural data upfront which comes from research, insights, and standards governing typical local behaviors in conjunction with data resulting from local user groups, testing sessions, and personas you have set up. On the other hand, you need to rely on customer feedback and sales data to capture the impact of your culturally sensitive tactics and the potential contrast between geographies. At the very least, you can figure out if your products and services should be managed in a leaner fashion and gauge whether AI and human intelligence should be rebalanced. For instance, you should decide between producing localized content with machine translation and having it done or edited by human linguists.
Broaden the Scope of Cultural Intelligence
Next, you need to broaden the scope and depth of cultural intelligence to cover end-to-end workflows. Although cultural intelligence may appear to be owned by multicultural marketing, or creative teams, ahead of a commercial launch, it comes into play at the very early stages of content and product lifecycles. Actually, it should be an ongoing goal of your global product leadership and content strategy. And cultural intelligence has to span functions and disciplines to be flawlessly incorporated in AI specifications.
There is no detail or glitch that has zero impact on customer experiences, product sales, or content accuracy. It is a comprehensive approach that determines the imprint of cultural intelligence. Recent examples of overlooked or underestimated cultural impact may be found in China. When Dolce & Gabbana used online ads featuring a Chinese woman trying to eat Italian food with chopsticks it made a number of local customers upset. Some thought chopsticks were being mocked. However, they are an undisputed symbol of the Chinese culture that cannot be subject to any kind of funny combination or light interpretation. In the same vein of cultural misuse, Burberry launched a controversial holiday campaign showing rather somber looking family members who seem quite unhappy whereas the Chinese Lunar New Year means optimism and happiness for families getting together.
Both cases underline the importance of cultural effectiveness throughout design, development, testing, certification, and deployment phases. They also point out the invaluable role that human resources can play to complement AI-powered optimization. It’s not just about cultural experts, but also leaders of technical and operational teams who can help prevent damage to your company’s brand.
Train More than Your Machines
Finally, you should train your internal resources on cultural intelligence as much as your machines and systems. AI implies more than upgrading processes, tools, and ecosystems. It requires new ways of thinking, collaborating, and organizing. You have to create or increase awareness among stakeholders and build knowledge among leaders. It may be quite difficult as they may focus on the immediate return on AI-enabled automation.
Therefore, you should bring forward the highly variable and evolving set of practices and habits triggering reach, resonance, and reaction for your customer base, as well as the need to integrate these drivers in AI-related decisions and technology. AI is as efficient and relevant as how you and your teams leverage it. If everyone contributes to instill emotional intelligence and develop it in AI agents, AI is going to ensure customer centricity by making content more deeply immersive and permanently appealing. That will be no artificial win.