Man + Machine: How can AI drive business growth?
Man and machine must work side by side to help businesses across all sectors grow.
Leentje Chavatte
Microsoft, Data & AI and Digital Transformation
While the hype of artificial intelligence (AI) and its potential role as a driver of transformational change to businesses and industries is pervasive, there are limited insights into what companies are actually doing to reap its benefits. The Artificial Intelligence Report, conducted by Ernst & Young, aims at getting a deeper understanding of how companies currently manage their AI activities, and how they address the current challenges and opportunities ahead.
To get to the heart of the AI agenda, we received input from AI leaders in 277 companies, across 7 sectors and 15 countries in Europe, via surveys and/or interviews. Below is a brief summary of what they had to say.
71% of the companies respond that AI is considered an important topic on the executive management level. This is significantly higher than on the non-managerial / employee level where AI is only considered an important topic in 28% of the companies. Interestingly, Board of Directors also came out lower with ‘only’ 38% of respondees reporting that AI is important to their board.
89% of the respondents expect AI to generate business benefits by optimizing their companies’ operations in the future. This is followed by 74% that expect AI to be key to engaging customers. This can be done by enhancing the user experience, tailoring content, increasing response speed, adding sentiment, creating experiences, etc.
C-suite respondents scored ‘engaging customers’ highest of the AI benefit areas. 100% Of the most advanced companies expect AI will help them engage customers, compared to only 63% of the less mature companies. Using AI to ‘transform products and services’ comes out slightly lower with 65%. ‘Empowering employees’ comes out the lowest with 60% of the companies expecting AI-generated benefits in that area.
57% of the companies expect AI to have a high or a very high impact on business areas that are “entirely unknown to the company today”. This is almost as much as AI is expected to impact the core of these companies’ current business. 65% is expecting AI to have a high or a very high impact on the core business. With AI presumably pushing companies into totally new domains in the future, it is perhaps not surprising that AI is receiving attention as a key topic for executive management.
Despite the apparent sizable impact that companies expect from AI, only a very small proportion of companies, constituting 4% of the total sample, self-report that AI is actively contributing to ‘many processes in the company and enabling quite advanced tasks today’ (referred to as ‘most advanced’ in this report).
Another 28% are in the ‘released’ stage where they have put AI selectively to active use in one or a few processes in the company. The majority, 51% of companies, are still only planning for AI or are in early stage pilots. 7% of companies are self-rated as least mature, indicating that they are not yet thinking about AI at this stage.
The most widely reported adoption of AI (47%) was in the IT/Technology function, followed by R&D with 36%, and customer service with 24%. Interestingly, several functions are hardly using AI at all; most notably, the procurement function, where only 4% of the companies currently use AI. This is followed by HR with 7% and product management with 9%. This is perhaps surprising, given the many use cases and applicable solutions in these functional areas.
When asking the respondents to rank the importance of 8 capabilities to enable AI in their businesses, ‘advanced analytics’ and ‘data management’ emerged as the most important. ‘AI leadership’ and having an ‘open culture’ followed.
When self-assessing the capabilities where the companies are least competent, they point to emotional intelligence and AI leadership. AI leadership is defined as the (lack of) ability to lead an AI transformation by articulating a vision, setting goals and securing broad buy-in across the organization. To summarize, the challenge ahead appears to be as much about culture and leadership as it is about data, analytics, and technology.