The Four Barriers to AI Adoption
AI adoption is slower than expected in many spaces. Some of the reasons are straightforward, but others are more subtle.
Most leaders wants to inject AI into their business to develop a competitive advantage. There are four challenges.
Also, because the systems are non-deterministic, they are unpredictable. The pace of innovation, the early understanding of AI internals, & the non-determinism compound to create doubt.
2. Security is the second challenge. Because of their unpredictable nature & because few have expertise launching these systems, product managers, engineering leaders, & security teams are hesitant to launch both internal & external systems until they develop confidence in data security.
AI security has at least four dimensions : model security, prompt injection, RAG authentication/authorization, & data loss prevention.
领英推荐
3. Legal is the next barrier to entry. Master service agreements (MSAs) are the contracts that dictate terms of service, data privacy, & service levels between a buyer & a vendor. These agreements’ clauses are well-trodden & known.
AI is new. Should a company allow a vendor to train a model using their data? Whose intellectual property is a fine-tuned model? What happens if a vendor violates the data privacy law? What training data is used that might subject the software buyer to future legal action?
Many legal teams are working to understand those questions.
4. Procurement is yet another barrier. SOC2, GDPR, ISO27001 & other certifications provide industry standards for security & compliance. But no such standard exists for AI - yet. Bias, fairness, & explainability are all important factors in AI : some are important for public relations, others for compliance.
Selling AI is not just selling software. Many of the processes are new & these barriers introduce friction into the sales process, extending sales cycles.
Over time, these rough edges will be worn smooth through practice. But the first companies selling today will need to persist through these challenges.
Entrepreneur, researcher, and technology commercialization expert. Doctorate in Business Economics. Ph.D. in Business Information Systems.
2 个月Excellent post, Tomasz! I want to add two points. First, we need quality proprietary data sets to build learn-and-tests circles using AI algorithms. Second, we must consider the challenges and opportunities of breaking AI-related IP and non-IP ownership chains.?Technically, these are perhaps the most significant barriers to mastering AI. #PROFITomix
Teaching Ai @ CompleteAiTraining.com | Building AI Solutions @ Nexibeo.com
4 个月Great article! The four challenges you highlighted are indeed pivotal in understanding AI adoption barriers. To overcome these, fostering cross-functional teams of experts in AI, security, legal, and procurement can be crucial. Also, AI can help by predicting potential security breaches, offering legal compliance insights, and streamlining procurement processes through automated checks. How do you see the future of AI governance evolving to address these multifaceted concerns? #AIEthics #AIGovernance #TechInnovation
Generative AI implementation | AI Strategist | C-Cuite Advisor & Board Member
4 个月One reason for slower AI adoption is a lack of basic awareness. Readers of AI articles and comments are often early adopters or fast followers, but this is not representative of the entire adoption cycle, which includes the early majority and laggards. Additionally, there are significant differences in the pressures faced by large corporations versus private companies. In my experience, the largest companies and even countries are constantly seeking a competitive “magic sword.” They are frequently pressured by investors demanding to know their AI strategy and asking when they will see results. Conversely, private companies are focused on their day-to-day operations. Without external pressures, they often view the AI hype as just another phase of the Gartner hype cycle and prefer to avoid it. Additionally I've noticed those industries that live and die by patents (i.e. pharmaceutical companies) are paranoid (and rightly so) that their secrets are added to the public record.
Creative thinker and Financial inclusion expert. Passionate about Sustainability driven by the uniqueness of our community. I help you build investor ready & inclusive businesses for growth. Visionary (DrumsRhythmic)
4 个月Every ignorant anti AI comments are the same comments and laughters that Internet Era was met. Some see barriers I see tools.
Seed stage venture capital investor in future of work, marketplaces, SaaS, and AI
4 个月Great thoughts Tomasz Tunguz. Agree these are clear considerstions.