MMC Ventures published a report on AI and the highlights for Use Cases and Buyers of AI have been summarized below.
Use Cases and Buyers of AI – Key Takeaways
- In 2019, AI crosses the chasm from early adopters to the early majority.
- AI adoption has tripled in 12 months- one in seven large companies has adopted AI.
- In the pst 2 years, 2/3’s of large companies will have live AI initiatives.
- In the course of three years, the proportion of enterprises with AI initiatives will have grown from one in 25 to one in three.
- Globally, China leads the race for AI adoption.
- Twice as many enterprises in Asia have adopted AI, compared with companies in North America, due to government engagement, a data advantage and fewer legacy assets.
- Early adopters (financial service and high-tech companies) maintain a lead while movers (retail, healthcare and media) are rapidly catching up. Government agencies, education companies and charities are laggards in AI adoption.
- Enterprises are using multiple types of AI application, with one in ten enterprises using ten or more. The most popular use cases are chatbots, process automation solutions and fraud analytics. Natural language and computer vision AI underpin many prevalent applications as companies embrace the ability to replicate traditionally human activities in software for the first time.
- Leaders and laggards face different adoption challenges – laggards are struggling to gain leadership support for AI and to define use cases. Leaders’ difficulties, in contrast, have shifted from ‘if’ to ‘how’. Leaders are seeking to overcome the difficulty of hiring talent and address cultural resistance to AI.
- AI initiation has shifted from the C-suite to the IT department – 2 years ago, CXOs initiated two thirds of AI initiatives. In 2019, as corporate engagement with AI shifts from ‘if’ to ‘how’, the IT department is the primary driver of AI projects.
- Companies prefer to buy, not build, AI. Nearly half of companies favor buying AI solutions from third parties, while a third intend to build custom solutions.
- Workers expect AI to increase the safety, quality and speed of their work. As companies’ AI agendas shift from revenue growth to cost reduction initiatives, however, workers are concerned about job security.
Use Cases and Buyers of AI – AI Adoption Has Tripled in 12 Months
Gartner says, “Today, 14% of enterprises have deployed AI. A further 23% intend to deploy AI within the next 12 months.”
Large companies are adopting AI at a rapidly accelerating rate. Just 4% of enterprises had adopted AI 12 months ago.
- Today, 14% of enterprises have deployed AI
- A further 23% intend to deploy AI within the next 12 months
- Adoption will continue to accelerate; in two years, nearly two thirds of large companies will have live AI initiatives
Use Cases and Buyers of AI – Most Popular AI Deployments
AI deployment is proliferating as:
- Widespread awareness of AI drives a growing volume of enterprise test-and-learn initiatives
- Early proof-of-concept projects mature, demonstrating value and catalyzing further investment
- Understanding of AI, although low, is improving and driving investment
- Maturing AI technology – and a burgeoning range of inexpensive or open source AI APIs, frameworks and tooling – lower barriers to entry
- Enterprises mitigate skills shortages by recruiting chief science officers, researchers, data scientists and machine learning engineers – and up-skilling existing employees
- Enterprises embrace a rich ecosystem of ‘best-of-breed’ third-party AI software suppliers
Use Cases and Buyers of AI – Most Popular AI Use Cases
The most popular AI use cases are:
- Chatbots (26% of enterprises)
- Process automation solutions (26%)
- Fraud analysis (21%)
Use Cases and Buyers of AI – AI Applications
Prevalent AI applications include:
- Consumer/market segmentation (15%)
- Computer-assisted diagnostics (14%)
- Call centre virtual assistants (12%)
- Sentiment analysis/opinion mining (12%)
- Face detection/recognition (11%)
- HR applications (e.g. CV screening) (10%)
Use Cases and Buyers of AI – AI Applications By Industry
Increasingly, certain AI applications are becoming widespread in particular industries
- Nearly four in ten healthcare providers use computer-assisted diagnostics
- Three in ten utilities use process automation tools
- Six in ten healthcare payers, nearly half of financial service firms and four in ten insurers use AI for fraud detection
- Three in ten retailers and a quarter of wholesalers use AI for consumer segmentation
- A third of media companies use AI for sentiment analysis
- Sector adoption is in flux
Adoption of AI is uneven – across and within sectors – and in a state of flux.
- Early adopters – sectors that proactively invested in AI – are reaping the benefits and maintaining their leadership. In 2017, financial services and high-tech & Telco companies anticipated increasing their investment in AI, in the following three years, more than companies in other sectors. Today, insurance, software & IT service and Telco companies lead in AI adoption.
- Movers have awoken to AI’s potential and are closing the adoption gap. In 2017, adoption of AI in retail, healthcare and media was moderate relative to other sectors. Adoption in these sectors has accelerated. More than four in ten retail, healthcare and media companies have now invested in AI or will have done so within 12 months.
- High rates of adoption in financial services, high-tech & Telco, retail, healthcare and media reflect the confluence of opportunity and engagement.
- Laggards – Government agencies, education companies and charities – are falling behind in AI adoption. While AI has potential to transform Government, in particular, given extensive data sets and numerous optimization opportunities,
- Divergence is evident within as well as across sectors. The proportion of Insurance companies that have adopted AI, or intend to within the next 12 months, is ten percentage points higher than other financial service companies. Within the healthcare sector, engagement with AI is greater among payers than providers.
Use Cases and Buyers of AI – AI Penetrating Departments
Interest in AI is diverging by department
McKinsey Global Institute states that “In approximately 60% of occupations, at least 30% of constituent activities are technically automatable by adapting currently proven AI technologies.”
- A gulf is emerging between departments’ interest in exploiting AI’s potential. While IT departments express the greatest interest in AI, customer service teams are emergent AI champions. The proportion of marketing, HR and finance departments interested in AI projects, meanwhile, is nearly double that of legal & compliance, sales and field service teams.
- Customer service teams’ interest in AI reflects AI’s value to both managers and workers, and low barriers to adoption. Customer service teams spend extensive time addressing repetitive, lower-value enquiries. AI, underpinned by natural language processing, enables replies to a growing proportion of enquiries to be created and sent automatically. For many other enquiries, contact center workers’ activities can be augmented through AI.
- Extensive interest in AI from marketers, similarly, reflects the breadth of marketing activities to which AI can be usefully applied and easily adopted. AI can augment customer segmentation, channel optimization, content personalization, price optimization and churn prediction. Extensive training data is available and accessible for each activity, while uplift can be readily quantified.
- Modest interest in AI from Legal & Compliance teams is at odds with AI’s potential for value in these departments. While companies’ legal and compliance costs are ballooning, AI powered by natural language processing can support activities including: automated time tracking; case law review; due diligence; litigation strategy; and communication compliance. Modest adoption of technology more broadly within legal departments, and cultural resistance to change, is inhibiting interest.
Use Cases and Buyers of AI – AI Ideal for Data Centric Use Cases
Data-centric sectors will see the greatest impact
- AI is being deployed in all sectors and to a wide variety of business processes. However, AI will have more numerous applications and greater impact in certain sectors
- AI’s impact will be greatest in sectors in which a large proportion of time is spent collecting or synthesizing data, or undertaking predictable physical work
These sectors include:
- Finance and insurance (50% of time)
- Retail, transport and trade (40% of time)
- Professional services (37% of time)
- Manufacturing (33% of time)
- Healthcare (33% of time)