In this post, I highlight some of the best thought-leadership articles and reports that cross my desk. I note why they rise to the top of the pile and are worth reading (or skimming), even if they focus on functions or industries outside your areas of interest. Among the criteria I use to make the selections are freshness and provocativeness of insights and timeliness, analytical rigor, depth of prescriptions, and overall readability.
The news is filled with talk of artificial intelligence (AI), prompted by the recent dissemination of the chatbot ChatGPT. Microsoft’s Bing search engine also introduced a chatbot feature powered by AI (and which has made some people who have tested it queasy) that has the potential to upend the search business.
These chatbots may have captured the broader public’s attention, but, more quietly, businesses across industries have begun to embed AI into their processes. Professional services firms are publishing extensively on how these enterprises can apply AI. (McKinsey also jumped in with some early pieces on generative AI, here and here.) Following are some of the more interesting pieces that firms have published on AI since mid-2022.
Back to top
These Accenture authors explore the use of AI in travel companies, although the report addresses issues that could interest executives in other industries. A survey found that only 13 percent of travel companies have achieved AI maturity, meaning they have positioned themselves to take
advantage of the full potential of the technology.
“The most promising applications for AI in travel in terms of transforming experiences,” the authors write, “include customized travel planning and online customer service through chatbots, face-to-face traveler service though robots, facial recognition and identity management through
biometrics, and dynamic pricing and predictive data analytics through AI and machine learning.”
Scaling AI pays off, no matter the investment”
BCG consultants assessed the AI maturity of more than 2,700 companies in three areas: AI use cases, AI capabilities, and the company’s digital foundation. Their research found that companies that invest more in digital also put more resources into AI, and for those that scale up AI, even small seed investments offer big returns.
They found that modest investments in specific AI use cases can generate up to 6 percent more revenue; with greater investment, the revenue impact from AI rises to 20 percent or more.
Leaders in scaling and generating value from AI do three things better than other companies, the authors found:
Accenture
BCG
The art of AI maturity in travel
leaves of absence. Some 60 percent of women compared with 45 percent of men have declined a role because of their caregiving responsibilities.
• “They make data and technology accessible across the organization, avoiding siloed and incompatible tech stacks and standalone databases that impede scaling.”
guide them.
• “They prioritize the highest-impact use cases and scale them quickly to maximize value.”
tech skills in particular—than men.
Fueling the AI transformation: Four key actions powering widespread value from AI, right now.
Deloitte
Deloitte publishes an annual “State of AI in the Enterprise” report. In this edition, the firm surveyed 2,680 business leaders on the status of their AI undertakings. The 2022 survey found that despite increased AI deployment, companies were still struggling to obtain solid results.
Companies that achieved better results pursued four key actions, according to the survey:
Invest in culture and leadership: “Leaders should embark on reinventing work to capitalize on the growing optimism and opportunity that their human workforce sees in AI. People are still at the core of a business’ success, and AI can help unleash the power of a combined human and machine workforce.”
Transform operations: “To ensure ethical and quality application of AI, the entire operating model may need to change to accommodate the unique capabilities of intelligent machines. Workflows and roles should be reevaluated to manage risk and achieve new value.”
Orchestrate tech and talent: “On the flip side of the culture and leadership coin, companies must develop their AI strategies in a tight talent market, with growing off-the-shelf platforms, tools, and accelerators that can jump-start a company’s transformation.”
Select high-value use cases: “AI is fueling transformations across all industries, and many leaders have begun to unlock which use cases are driving the most value within their given context. The important takeaway is to orchestrate a strategy of both near- and long-term differentiating applications of AI.”
“
• “They recognize the importance of aligned leadership and employees who build and leverage AI, and they support staff who promote collaboration and end-to-end agile product delivery.”
The state of AI in 2022—and a half decade in review”
McKinsey
McKinsey based its review of the state of AI in 2022 on a survey of 1,492 participants across regions and industries. The survey found that adoption of AI had more than doubled since 2017 but that uptake had remained between 50 and 60 percent for the past few years.
“We might be seeing the reality sinking in at some organizations of the level of organizational change it takes to successfully embed this technology,” one author wrote. “In our work, we’ve encountered companies that get discouraged because they went into AI thinking it would be a quick exercise, while those taking a longer view have made steady progress by transforming themselves into learning organizations that build their AI muscles over time. These companies gradually incorporate more AI capabilities and stand up increasingly more applications progressively faster and more easily thanks to lessons from past successes as well as failures.”
What makes this one of the stronger articles is the authors’ use of examples to show how AI could be used in an industrial setting:
AI scheduling agents: “Some of the most difficult challenges for industrial companies are scheduling complex manufacturing lines, maximizing throughput while minimizing changeover costs, and ensuring on-time delivery of products to customers. AI can help through its ability to consider a multitude of variables at once to identify the optimal solution. In one metals manufacturing plant, an AI scheduling agent was able to reduce yield losses by 20 to 40 percent while significantly improving on-time delivery for customers.”
Knowledge discovery: “Many industrial companies face the common issue of identifying the most relevant data when faced with a specific challenge. AI can accelerate this process by ingesting huge volumes of data and rapidly finding the information most likely to be helpful to the engineers when solving issues. For example, companies can use AI to reduce cumbersome data screening from half an hour to a few seconds, thus unlocking 10 to 20 percent of
productivity in highly qualified engineering teams.”
AI-enabled product system design: “For many industrial companies, the system design of their products has become incredibly complex. Organizations can use AI to augment a product’s bill of materials with data drawn from its configuration, development, and sourcing. This process
identifies opportunities to reuse historical parts, improve existing standard work, and support preproduction definition. With these insights, companies can significantly reduce engineering hours and move to production more quickly.”
The article also notes the use of AI in product-performance optimization and root-cause analysis.
“
The AI revolution in banking
Oliver Wyman
These Oliver Wyman authors focus on how banks can use AI to obtain a competitive edge and identify the steps necessary to succeed. (In a related article, McKinsey authors look at the use of AI in building successful neo-banks.)
“For some banks that have embraced AI, the results have been impressive,” the authors wrote. “Our recent work with a leading bank serves as a testimony of the financial impact that AI can deliver. As an example, the introduction of AI in selection of leads for marketing campaigns has
had remarkable results: 10% of sales in the bank today for personal loans and auto loans are linked to AI campaigns. In yet another example, leveraging advanced data analytics to optimize pricing yielded up to a 5% increase in net income in personal loans. Application of AI in other
areas, risk and call center optimization, is underway with similar results expected.”
“The future is now: Unlocking the promise of AI in industrials”
