While AI is widely implemented across industries, only 26% of companies have developed the full capabilities needed to move past pilot projects and generate concrete value, says a recent study by Boston Consulting Group (BCG).
The report, Where’s the Value in AI?, is based on insights from a comprehensive survey involving 1,000 executives from over 20 industries, spanning 59 countries.
According to BCG, just 4% of companies have reached advanced Artificial Itelligence maturity and generate significant value. An extra 22% have a developed Artificial Intelligence strategy, strong capabilities, and are starting to see real gains. BCG labels these companies as “AI leaders.” The remaining 74% still struggle to derive tangible returns from AI, indicating significant gaps in AI implementation.
AI LEADERS SET HIGH GOALS AND FOCUS ON CORE FUNCTIONS
“AI leaders are raising the bar with ambitious goals,” said BCG’s senior partner, Nicolas de Bellefonds. Leaders focus on driving impact through key business transformations rather than minor productivity improvements. Over the last three years, Artificial Intelligence leaders have outperformed other companies, achieving 1.5 times higher revenue growth and 1.6 times better shareholder returns.
KEY CHARACTERISTICS OF AI LEADERS
The report highlights six critical traits that set AI leaders apart:
Artificial Intelligence leaders leverage AI in core business areas and support functions, with core processes driving 62% of AI value.
They make significant investments in AI. They assign double the resources and focus on workforce enablement. Leaders expect Artificial Intelligence to drive 60% more revenue growth and 50% greater cost savings by 2027.
Leaders integrate AI to streamline costs across functions, with 45% of them applying AI in cost transformation. They also focus on revenue generation, with one-third actively using AI to boost sales.
AI leaders strategically limit AI projects to promising, high-impact areas. They scale twice as many Artificial Intelligence solutions and expect twice the ROI in 2024 compared to other companies.
For AI leaders, the success formula is 70% investment in people and processes, 20% in technology, and 10% in algorithms.
Leaders embrace generative Artificial Intelligence (GenAI). It aids in content creation and complex reasoning. This drives innovation in industries that rely on qualitative data.
INDUSTRIES LEADING IN AI ADOPTION
Certain sectors have higher concentrations of Artificial Intelligence leaders, particularly those that experienced early digital disruption. In fintech, 49% are classified as leaders, followed by software (46%) and banking (35%). These sectors have robust digital infrastructures that allow effective Artificial Intelligence integration.
CORE BUSINESS FUNCTIONS DRIVE MAJORITY OF AI’S VALUE
BCG’s report challenges the view that AI’s primary value lies in support functions. In fact, 62% of Artificial Intelligence -generated value comes from core functions. These include operations (23%), sales and marketing (20%), and research and development (R&D) (13%). Support functions account for only 38%, with customer service, IT, and procurement leading value creation within this group.
INDUSTRY-SPECIFIC ARTIFICIAL INTELLIGENCE VALUE DRIVERS
The survey highlights variations in Artificial Intelligence’s impact across industries:
- Sales and Marketing: Several industries report AI’s significant impact on their operations. Software leads with 31%. Travel and tourism also account for 31%. Media follows at 26%, while telecommunications stands at 25%.
- Research and Development: Biopharma (27%), medtech (19%), and automotive (29%) sectors gain heavily from Artificial Intelligence in R&D.
- Customer Service: Artificial Intelligence has notable value in customer service for insurance (24%) and banking (18%).
- Personalization in Consumer Sectors: Retail (22%) and consumer products (19%) report high gains from Artificial Intelligence -powered personalization.
IMPLEMENTING THE 70-20-10 AI PRINCIPLE
BCG’s research shows that most Artificial Intelligence implementation challenges stem from people and processes, accounting for 70%. Technology accounts for 20%, and only 10% of challenges are due to algorithm issues. The 70-20-10 principle emphasizes focusing on people-related capabilities. These include change management, workflow improvement, and Artificial Intelligence talent. It advises against over-prioritizing technical components.
BARRIERS TO SCALING Artificial Intelligence ACROSS ORGANIZATIONS
Scaling Artificial Intelligence across organizations requires addressing core issues beyond technology. Key factors for successful AI scaling include:
- Change Management: Creating a culture open to Artificial Intelligence integration.
- Workflow Improvement: Enhancing efficiency in core processes.
- Artificial Intelligence Talent and Governance: Building specialized Artificial Intelligence teams with clear governance.
- Data Quality and Management: Ensuring reliable, high-quality data for Artificial Intelligence models.
Cost of Falling Behind in Artificial Intelligence
Amanda Luther, BCG’s partner and coauthor, warns that companies failing to focus on people-centered AI initiatives may fall further behind. “Three-quarters of companies have yet to unlock Artificial Intelligence’s value,” she said. BCG advocates allocating two-thirds of resources to people-related initiatives, with the remaining third focused on technology and algorithms.