KEKST CNC
Viva Tech Prelude | State of affAIrs
Sean Evins
Partner, AI & Emerging Technology
May 2025
Overview
What is AI?
Artificial Intelligence (AI) refers to the ability of computer systems to perform tasks and mimic behaviours that typically require human intelligence, such as understanding, learning, problem-solving, decision-making, and actioning. AI encompasses a range of technologies and disciplines, including:
- Machine Learning
- Robotics
- Computer Vision
- Generative AI
- Deep Learning
- Natural Language Processing
Narrow AI
What we have now:
- ChatGPT generating text
- Spotify recommending music
- Social media surfacing content
- Google Maps giving directions
General AI
What may come:
- Also known as “AGI” (Artificial General Intelligence)
- Human-level thinking
- Capable of learning anything, reasoning across topics, and adapting to new situations
- Able to apply knowledge and skills learned to new domains
Limitations?
AI is only as good as its training. For example, when prompted with: “Using DALL-E, create an image of a clock showing 3:15,” the results may not always be accurate, highlighting the limitations of current AI models.
Where we are
There are predictable cycles to technological change. The Gartner Hype Cycle for Artificial Intelligence (2023) illustrates how expectations rise and fall over time for various AI technologies:
- Innovation Trigger: First-Principles AI, Automatic Systems, Multiagent Systems, Neuro-Symbolic AI, Causal AI, AI Simulation, AI Engineering, Data-Centric AI, Composite AI, Operational AI Systems, AI TRISM, Decision Intelligence, Artificial General Intelligence, Prompt Engineering, Neuromorphic Computing, Responsible AI, Smart Robots
- Peak of Inflated Expectations: Generative AI, Foundation Models
- Trough of Disillusionment: Synthetic Data, ModelOps, EdgeAI, Knowledge Graphs, AI Maker and Teaching Kits
- Slope of Enlightenment: Cloud AI Services, Intelligent Applications, Autonomous Vehicles, Data Labeling and Annotation
- Plateau of Productivity: Computer Vision
Legend:
Plateau will be reached in less than 2 years, 2 to 5 years, 5 to 10 years, more than 10 years, or will become obsolete before plateau.
As of July 2023.
Some get it wrong.
Historical Examples:
- Horse vs. Automobile: Early advertisements cautioned against abandoning horses for automobiles, citing costs and reliability concerns. For example, Ed. Klein of 732 Massachusetts Street argued that horses were more dependable and cost-effective than cars.
- Telephone Industry vs. Internet Phone Software: In the 1990s, the telephone industry sought to ban Internet phone software, fearing unfair competition. Despite early skepticism, computer-to-computer voice communication became standard, as predicted by Marc Andreessen of Netscape.
- Expert Misjudgment: Nobel Prize-winning economist Paul Krugman stated in 1998, “By 2005 or so, it will become clear that the Internet's impact on the economy has been no greater than the fax machine's.”
What are corporate leaders saying?
- “Artificial intelligence will have a more profound impact on humanity than fire, electricity and the internet.” — Sundar Pichai, CEO of Alphabet
- “At least 40% of all businesses will die in the next 10 years... if they don't figure out how to change their entire company to accommodate new technologies.” — John Chambers, Cisco
Past 3 years: An AI whirlwind
- 2022: ChatGPT debuts, reaching 1 million users in 5 days
- 2023: AI emerges as a national security issue (U.S. executive order, US/China chip restrictions)
- 2024: Every major tech firm launches a large language model (LLM); enterprise adoption of GenAI tools accelerates; AI infrastructure race heats up; multi-modality in GenAI
- 2025: AI becomes a C-suite agenda item: business strategy, communications, compliance, policy, ethics; “Deep Seek” and questions over infrastructure spending, open-source vs. proprietary; AI legislation and regulatory guardrails accelerate
AI isn’t coming — it’s here. But are we ready for it?
What we're seeing: Quick Look
Some data to consider:
- 40% of corporate communications teams piloted AI tools in 2024
- 75% of corporate leaders will make changes to their talent strategies in the next 2 years
- 3,000% expected increase in deepfake-related fraud by approximately 2026
- 60+ jurisdictions actively drafting AI-specific regulations
- 97% of executives expect AI to be transformative to their business
- 82% of companies are now exploring GenAI solutions
- Only 28% have clear governance plans in place
What's happening? AI trends we’re watching
Enterprise Integration
- AI is being embedded in Microsoft enterprise suite, Google Workspace, and other day-to-day applications, playing a much larger role in business operations.
Synthetic Media
- There is a rapid increase in the quality of deepfakes, voice clones, and auto-generated videos, which are now nearly indistinguishable from human-created content.
Shift to Specific
- Following the success of LLMs, there is a wave of domain-specific models trained on specialized data, offering better accuracy, compliance, and relevance.
Data Battleground
- High-quality, proprietary data is becoming the competitive edge for AI performance and differentiation. Having a clear data strategy is now critical.
Changing Search
- Generative AI is changing how we search and find information, upending a 20-year constant in information retrieval.
What's happening? Geopolitical trends to consider
AI Nationalism
- US-China arms race (e.g., Deep Seek)
- National investment into data centers and compute
- Data sovereignty shaping governance frameworks
Regulation Fragmentation
- EU AI Act vs. fractured U.S. approach vs. China’s control-first model
- Balancing innovation with control and values
Mis/Disinformation & Integrity
- The rise of synthetic media and AI-powered influence campaigns is a growing concern for democratic and corporate stability.
AI as a Strategic Asset
- Growing investment in AI for core military and defense capabilities
- Raises questions for public-private partnerships and ethics
Power Rebalancing
- Emerging economies are leveraging AI to leapfrog traditional development pathways, shifting the balance of influence and creating new blocs
What this means: Why this matters now
AI is the biggest corporate and reputational shift moment in the last 25 years. It is expected to transform industries faster than any other technology in history.
- Competitive Positioning
- Reputation & Trust
- Regulation & Risk
AI is not just a tech issue. It is a boardroom issue tied to corporate governance, risk, communications, and strategy.
Opportunities: Future-proofing your business
- Strengthen brand trust through ethical AI governance
- Build regulatory readiness into the “Corporate DNA”
- Turn proprietary data into a competitive moat
- Upskill teams and embed AI into core functions
- Monitoring, strategic intelligence, and competitive benchmarking
Risks & Challenges: Things to consider, and prepare for
- Reputational risks from AI missteps
- Regulatory & compliance uncertainty
- Data quality, governance, and liability
- Talent, organizational readiness, and change management
- Over-reliance on black-box systems
Questions to consider: How ready are you?
- Do we have a clear, company-wide AI narrative?
- Are we prepared for regulatory, ethical, and reputational scrutiny?
- How are geopolitical shifts affecting our strategies?
- Are our executives, board, and spokespeople literate on AI?
- Are we using AI to enhance our team capabilities?
Thank you!
Sean Evins
Partner, AI & Emerging Technology
Sean.Evins@kekstcnc.com