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The Race is On: AI Gets Real, Slow and Steady Wins the Race
AI adoption is progressing cautiously across various sectors, with companies prioritising careful deliberation over rapid transformation.
Published
22 hours agoon
By
AIinAsia
TL/DR:
- AI adoption is progressing cautiously across various sectors, with companies prioritising careful deliberation over rapid transformation.
- Industries like healthcare and legal services are facing challenges in integrating AI due to inconsistencies and the need for human oversight.
- The tech and visual design sectors are seeing significant AI integration, with predictions of AI handling up to 80% of coding tasks by next year.
In the wake of ChatGPT’s dramatic arrival two years ago, companies are excited about generative AI’s possibilities but heading into 2025 with careful deliberation rather than rushing to transform their operations. The Channel Tunnel, one of the world’s most strained travel checkpoints, presents a compelling example of AI’s current limitations and practical applications.
Each day, 400 of the world’s largest locomotives cross the tunnel linking France and Britain, with nearly 11 million rail passengers and 2 million cars carried through annually. For GetLink, the company managing the 800-meter-long trains, caution around AI implementation remains paramount.
“We’re in a highly regulated business. We’re not kidding around. These are very strict procedures.”
Rather than controlling train operations, their AI primarily handles more mundane tasks like searching through rules and regulations. The legal sector, initially viewed as prime for AI disruption, tells a similar story.
“ChatGPT is obviously incredible. But it’s really quite hard to apply it in your day-to-day workflows in a way that is impactful,” noted James Sutton, founder and CEO of Avantia Law.
While AI excels at basic tasks like searching legal databases and generating simple summaries, more complex work requires careful human oversight.
Sutton explained that AI’s inconsistency remains a challenge:
“One contract I can put in and the AI kicks it out perfectly. Another one will be 40 percent right. That lack of certainty means lawyers still have to verify everything.”
The tech industry presents a more aggressive adoption curve. Google reports that 25 percent of its coding is now handled by generative AI. JetBrains CEO Kirill Skrygan predicts that by next year, AI will handle about 75-80 percent of all coding tasks.
“Developers are using AI as assistants to generate code, and these numbers are growing every day,” said Skrygan at the Web Summit in Lisbon. “The next level is coding agents that can resolve entire tasks usually assigned to developers.”
He suggested that over time, these agents could replace virtually all of the world’s millions of developers. Visual design industries, particularly fashion, are seeing significant impact from AI image generators like DALL-E, Midjourney, and Stable Diffusion. These tools are already transforming work habits and shortening time-to-market for new collections.
In healthcare, despite a study showing AI’s potential —including one where ChatGPT outperformed human doctors in diagnosis from case histories — practitioners remain hesitant to fully embrace the technology.
“They didn’t listen to AI when AI told them things they didn’t agree with,” Dr. Adam Rodman, who carried out the study, told the New York Times.
Companies face a complex calculation between innovation, prudence and how much they are willing to spend.
“It will take some time for the market to sort out all of these costs and benefits, especially in an environment where companies are already feeling hesitation around technology investments.”
Anant Bhardwaj, CEO of Instabase, believed that AI’s limitations were real but temporary.
“The real new innovation, like new physics or new ways of space exploration, those are still beyond the reach of AI… If people think that AI can solve every single human problem, the answer today is ‘No.’”
While AI excels at processing existing patterns and data, Bhardwaj argued it lacks the human curiosity needed to explore truly new frontiers. But he predicted that within the next decade, most industries will have some form of AI-driven operations, with humans in the backseat, but complete AI autonomy remains distant. Still, the disruption caused by AI is coming hard and fast, and countries must be prepared.
“White collar process work is hugely impacted, that’s already happening. Call centers is already happening,” Professor Susan Athey of Stanford University told a statistics conference at the IMF.
Athey, an economist of the tech industry, expressed worry about regions where a core profession such as call centers risked being swept away by AI.
“Those are ones I would really watch very carefully. Any country that specialises in call centers, I’m very concerned about that country,” she said.
The Cautious Approach to AI Adoption
- Regulated Industries: Sectors like transportation and legal services are adopting AI cautiously, focusing on mundane tasks while ensuring strict regulatory compliance.
- Tech Industry: The tech sector is more aggressive in AI adoption, with predictions of AI handling up to 80% of coding tasks by next year.
- Visual Design: AI image generators are transforming the fashion industry, shortening time-to-market for new collections.
AI in Healthcare: Potential and Challenges
- Diagnostic Capabilities: AI has shown potential in healthcare, outperforming human doctors in some diagnostic tasks.
- Hesitancy: Practitioners remain hesitant to fully embrace AI due to inconsistencies and the need for human oversight.
- Future Prospects: While AI’s limitations are real, its impact on healthcare is expected to grow, albeit slowly.
The Economic Impact of AI
- White Collar Jobs: AI is significantly impacting white collar process work, including call centers.
- Economic Concerns: Countries specialising in call centers are at risk of being swept away by AI, raising economic concerns.
- Preparedness: Nations must be prepared for the disruption caused by AI, ensuring economic stability and job security.
Looking Ahead: The Future of AI
- Industry Integration: Within the next decade, most industries will have some form of AI-driven operations.
- Human Oversight: Complete AI autonomy remains distant, with humans still needed for oversight and decision-making.
- Innovation: AI’s limitations in exploring new frontiers highlight the need for human curiosity and innovation.
As we navigate the exciting yet complex landscape of AI, it is crucial for us to approach its adoption with caution and deliberation. While AI offers immense potential, it also presents challenges that require careful consideration. Our cautious approach ensures that we maintain regulatory compliance, address inconsistencies, and prioritise human oversight. This balanced strategy will enable us to harness AI’s benefits while mitigating risks, paving the way for a sustainable and innovative future.
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Amazon’s Nova Set to Revolutionise AI in Asia?
Amazon’s Nova AI models are set to revolutionise the AI landscape in Asia with their multimodal generative capabilities.
Published
1 day agoon
December 4, 2024By
AIinAsia
TL;DR:
- Amazon Web Services (AWS) has launched Nova, a family of multimodal generative AI models, including text, image, and video generation capabilities.
- Nova models are optimised for speed, cost, and accuracy, with context windows supporting up to 2 million tokens by early 2025.
- AWS is planning to release speech-to-speech and any-to-any models in 2025, expanding Nova’s capabilities.
Amazon Web Services (AWS) has today made a groundbreaking announcement that may just revolutionise the industry
At its re:Invent conference, AWS unveiled Nova, a new family of multimodal generative AI models that promise to push the boundaries of what is possible with AI. This article delves into the capabilities of Nova, its potential impact on the AI landscape in Asia, and what the future holds for this innovative technology.
The Nova Family: A Comprehensive Suite of AI Models
The Nova family comprises four text-generating models—Micro, Lite, Pro, and Premier—each designed to cater to different needs and capabilities. Additionally, Nova Canvas and Nova Reel are dedicated to image and video generation, respectively.
Text-Generating Models: Micro, Lite, Pro, and Premier
- Micro: Optimised for speed, Micro can process and generate text with the lowest latency, making it ideal for quick responses.
- Lite: Capable of handling image, video, and text inputs, Lite offers a balanced mix of speed and versatility.
- Pro: Provides a balanced combination of accuracy, speed, and cost, suitable for a range of tasks.
- Premier: The most capable model, designed for complex workloads and creating tuned custom models.
“We’ve continued to work on our own frontier models,” Jassy said, “and those frontier models have made a tremendous amount of progress over the last four to five months. And we figured, if we were finding value out of them, you would probably find value out of them.”
Image and Video Generation: Canvas and Reel
- Canvas: Allows users to generate and edit images using prompts, with controls for colour schemes and layouts.
- Reel: Creates videos up to six seconds in length from prompts or reference images, with adjustable camera motion for pans, rotations, and zoom.
“[We’re trying] to limit the generation of harmful content,” he said.
Capabilities and Safeguards
Nova models are optimised for 15 languages, with a primary focus on English. They offer varying context windows, with Micro supporting up to 100,000 words and Lite and Pro supporting around 225,000 words. By early 2025, certain Nova models will expand to support over 2 million tokens, enhancing their processing capabilities.
AWS has implemented safeguards to ensure responsible use, including watermarking and content moderation. These measures aim to combat misinformation and harmful content generation.
Future Developments
AWS is already looking ahead, with plans to release a speech-to-speech model in Q1 2025 and an any-to-any model by mid-2025. These models will further expand Nova’s capabilities, enabling it to interpret verbal and nonverbal cues and deliver natural, human-like voices.
“You’ll be able to input text, speech, images, or video and output text, speech, images, or video,” Jassy said of the any-to-any model. “This is the future of how frontier models are going to be built and consumed.”
Wrapping Up: The Future of AI in Asia
The launch of Nova marks a significant milestone in the AI landscape, particularly in Asia. With its multimodal capabilities and focus on responsible use, Nova is poised to revolutionise industries ranging from content creation to data analysis. As AWS continues to innovate, the future of AI in Asia looks brighter than ever.
Join the Conversation
What excites you the most about Amazon’s Nova models? How do you envision these technologies shaping the future of AI in Asia? Share your thoughts and experiences with AI technologies in the comments below. Don’t forget to subscribe for updates on AI and AGI developments here. We’d love to hear your insights and continue the conversation!
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Navigating an AI Future in Asia with Cautious Optimism
Explore the measured approach to AI adoption in Asia, focusing on practical applications and future trends in AI implementation.
Published
3 days agoon
December 2, 2024By
AIinAsia
TL;DR:
- Companies are embracing AI with caution, focusing on practical applications rather than rushed transformations.
- AI excels in tasks like coding and visual design but faces challenges in regulated industries like healthcare and law.
- The future of AI is promising, but complete autonomy and solving all human problems remain distant goals.
In the wake of ChatGPT’s dramatic arrival two years ago, the landscape of artificial intelligence (AI) has seen both rapid advancements and cautious implementations. As we head into 2025, companies are excited about generative AI’s possibilities but are approaching its integration with careful deliberation rather than rushing to transform their operations. This measured approach is evident across various sectors, from transportation to healthcare, highlighting the practical applications and current limitations of AI.
Different countries are adopting AI at different rate (credit: Appier)
AI in the Legal Sector: Promise and Challenges
The legal sector, initially viewed as prime for AI disruption, tells a similar story of cautious adoption. While AI excels at basic tasks like searching legal databases and generating simple summaries, more complex work requires careful human oversight.
“ChatGPT is obviously incredible. But it’s really quite hard to apply it in your day-to-day workflows in a way that is impactful.”
Sutton explained that AI’s inconsistency remains a challenge:
“One contract I can put in and the AI kicks it out perfectly. Another one will be 40 percent right. That lack of certainty means lawyers still have to verify everything.”
This highlights the need for human oversight in ensuring the accuracy and reliability of AI-generated outputs.
Tech Industry: Aggressive AI Adoption
The tech industry presents a more aggressive adoption curve for AI. Google reports that 25 percent of its coding is now handled by generative AI, and JetBrains CEO Kirill Skrygan predicts that by next year, AI will handle about 75-80 percent of all coding tasks.
“Developers are using AI as assistants to generate code, and these numbers are growing every day. The next level is coding agents that can resolve entire tasks usually assigned to developers.”
He suggested that over time, these agents could replace virtually all of the world’s millions of developers. This aggressive adoption is driven by the potential for increased efficiency and productivity in the tech sector.
Healthcare: Hesitant Embrace of AI
In healthcare, despite a study showing AI’s potential—including one where ChatGPT outperformed human doctors in diagnosis from case histories—practicers remain hesitant to fully embrace the technology.
“They didn’t listen to AI when AI told them things they didn’t agree with.”
This hesitancy is driven by the need for absolute accuracy and reliability in healthcare, where human oversight remains crucial.
The Future of AI: Promising but Distant
Companies face a complex calculation between innovation, prudence, and how much they are willing to spend. While AI excels at processing existing patterns and data, it lacks the human curiosity needed to explore truly new frontiers.
“The real new innovation, like new physics or new ways of space exploration, those are still beyond the reach of AI… If people think that AI can solve every single human problem, the answer today is ‘No.’”
Bhardwaj predicted that within the next decade, most industries will have some form of AI-driven operations, with humans in the backseat, but complete AI autonomy remains distant.
Preparing for AI Disruption
The disruption caused by AI is coming hard and fast, and countries must be prepared. White-collar process work and call centres are already seeing significant impacts from AI.
Quote: “Those are ones I would really watch very carefully. Any country that specialises in call centres, I’m very concerned about that country.”
This highlights the need for countries to adapt and prepare for the inevitable disruption that AI will bring to various industries.
Farther Away: The Channel Tunnel
The Channel Tunnel, a critical travel checkpoint between France and Britain, serves as a compelling example of AI’s current limitations and practical applications. Each day, 400 of the world’s largest locomotives cross the tunnel, carrying nearly 11 million rail passengers and 2 million cars annually. For GetLink, the company managing these operations, caution around AI implementation remains paramount.
“We’re in a highly regulated business. We’re not kidding around. These are very strict procedures.”
Rather than controlling train operations, GetLink’s AI primarily handles more mundane tasks like searching through rules and regulations. This cautious approach ensures that critical operations remain under human oversight, while AI assists in streamlining administrative tasks.
Wrapping Up: The Road Ahead for AI
As AI continues to evolve, the road ahead is filled with both promise and challenges. Companies are embracing AI with caution, focusing on practical applications rather than rushed transformations. While AI excels in tasks like coding and visual design, it faces challenges in regulated industries like healthcare and law.
The future of AI is promising, but complete autonomy and solving all human problems remain distant goals (for now).
Join the Conversation
What are your thoughts on the future of AI in Asia? How do you think AI will transform your industry in the coming years? Share your experiences and insights in the comments below, and don’t forget to subscribe for updates on AI and AGI developments here. Let’s build a community of AI enthusiasts and stay ahead of the curve together!
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Adrian’s Arena: When Will AI Replace the CMO?
AI is transforming marketing while highlighting the irreplaceable role of Chief Marketing Officers (CMOs) in strategy, creativity, and EQ.
Published
3 weeks agoon
November 15, 2024
TL;DR
- AI Enhances but Doesn’t Replace CMOs: AI excels at data analysis and automation, but lacks the strategic vision, creativity, and emotional intelligence that CMOs bring to brands.
- AI Empowers Data-Driven Decisions: Machine learning helps CMOs make precise, effective marketing decisions by segmenting audiences and predicting trends.
- CMOs Balance AI with Human Insight: While AI meets Gen Z’s desire for instant gratification, CMOs ensure brands maintain deeper connections and values-driven messages.
Exploring the Possibilities of AI Replacing the CMO
I recently had the fortune to reconnect with an old friend who was travelling through my hometown. Something of an AI skeptic, well at least the impact of AI, we eventually got to pondering the positions of CSuites here in Asia.
With AI now a core part of modern marketing, could AI replace the Chief Marketing Officer (CMO)?
The reach of AI—processing data, automating tasks, personalising messages—is making marketing more efficient than ever. Yet, there’s something deeply human about the qualities a CMO brings to a brand: strategic vision, creativity, and emotional intelligence.
In this article, the first in a series of articles exploring the slightly terrifying closer look at what AI can and can’t do – especially when it comes to the leadership – we will explore whether the role of a CMO, which is required to drive meaningful connections, is one which only a human can truly fulfil. And let’s not forget, Gen Z’s unique approach to brands means the CMO role is only becoming more essential…
AI’s Expanding Role in Marketing: Capabilities and Current Limitations
- Enhanced Capabilities, Not a Replacement: AI brings exciting possibilities for marketers, like being able to sift through huge datasets, automate tasks, and deliver personalised experiences that feel like they’re just for you. CMOs now have more support than ever to make informed decisions, spotting trends faster and refining campaigns in real time. It’s a far cry from the manual analysis days, and it means that CMOs can now spend more time focusing on high-level strategy and creativity rather than number-crunching.
- Data-Driven Decisions with a Personal Touch: The way AI empowers CMOs to be data-driven is unprecedented. With machine learning picking up on subtle consumer behaviours, marketing can be precise and effective. Algorithms help segment audiences down to a granular level, meaning CMOs can target more thoughtfully than ever. Predictive analytics also gives CMOs that valuable ability to get ahead of trends, guiding campaigns with a proactive, rather than reactive, touch.
- Streamlining Campaigns and Automating Customer Interactions: AI has been a game-changer for campaign management and customer interactions. AI-driven platforms handle ad targeting, email campaigns, content personalisation, and customer service automation 24/7, all without breaking a sweat. This allows marketers to focus on the big picture—brand growth, innovation, and creativity—leaving the executional tasks in AI’s capable hands.
Generative AI can even spark new content ideas based on real-time data, but when it comes to defining the “why” behind a campaign, only a human CMO has the vision to make it resonate.
The Evolving Responsibilities of CMOs in an AI-Driven Landscape
Leading AI Integration with Innovation
Today’s CMO isn’t just responsible for traditional marketing; they’re at the forefront of adopting AI and blending it seamlessly into the marketing strategy. Getting it right means balancing what AI offers with the brand’s voice and values. AI is powerful, but without careful oversight, it can lose sight of what makes a brand unique.
A CMO’s job is now to ensure that AI is part of the mix, but never the entire recipe.
Creativity and Automation in Tandem
While AI excels at the technical stuff—analysing data, segmenting audiences, automating repetitive tasks—it simply doesn’t have the creative intuition or emotional intelligence that makes a brand truly memorable. A CMO’s creativity involves cultural understanding, subjective decision-making, and an ability to weave the brand’s unique personality into every campaign.
As AI takes on more routine tasks, CMOs are doubling down on creativity to ensure the brand feels consistent, authentic, and connected to its audience.
Upskilling the Marketing Team
As AI becomes central to marketing, CMOs have an important role in upskilling their teams. Experimentation, learning, and adaptability are essential mindsets as marketers embrace new tools and methodologies. A CMO fosters a team culture that values continuous learning, empowering marketers to embrace the potential of AI rather than fear it.
AI literacy is no longer optional—it’s a core skill in modern marketing.
Understanding Gen Z’s Transactional Nature and AI’s Role
- Instant Gratification and Transactional Expectations: Gen Z and Gen Alpha are changing the marketing game. They value speed and efficiency, often more than brand loyalty itself. For them, convenience and authenticity go hand in hand, and they don’t want to be kept waiting.
- Seamless: AI is ideal for delivering these seamless, hyper-personalised experiences, making interactions as quick and efficient as Gen Z expects.
The CMO’s Balancing Act: Speed and Substance
AI may deliver efficiency, but CMOs know it’s crucial not to lose the substance that makes a brand meaningful. While AI meets Gen Z’s desire for instant gratification, it can’t create the deeper connection that leads to brand loyalty. Gen Z are also incredibly socially conscious; they want brands to be clear about their values and stand for something beyond profit.
Here, the CMO is pivotal in ensuring the brand message is values-driven, adding layers of meaning and purpose to AI-driven interactions.
Using AI to Craft Values-Driven Messages
AI can gather insights into Gen Z’s preferences and behaviours, helping CMOs create messages that speak to these values without compromising on speed and personalisation. By blending AI’s strengths with human insight, CMOs deliver not just efficiency, but authenticity and relevance—qualities that keep Gen Z engaged and invested.
Could AI Replace the CMO or the Marketing Team? The Future of Marketing Roles
Automating Execution, Not Strategy
Many traditional marketing tasks—customer segmentation, ad targeting, A/B testing, and even some content creation—are increasingly automated by AI. Tools that personalise customer journeys or generate content on the fly make these tasks easier, but they’re still not a substitute for human insight.
AI may streamline execution, but it’s the CMO’s strategic vision that brings these campaigns to life.
Data Analysts and Market Researchers
AI is excellent for crunching numbers, but it needs the human touch to interpret those findings meaningfully. Human analysts bring a contextual understanding to data that AI lacks, especially in fast-changing markets where intuition and experience are invaluable.
AI may spot patterns, but people make sense of them, seeing what AI cannot.
The Creative Team
While AI can support design, copywriting, and content production, it doesn’t replace the creative direction, cultural awareness, or originality that human creatives provide. Generative AI tools are amazing for sparking ideas or suggesting variations, but a brand’s story needs human depth and originality. Creatives add the layers that make a campaign resonate.
AI Limitations in Cross-Cultural Contexts
When marketing across diverse regions, understanding cultural nuances is essential. AI can pick up on trends, but without context, it can misinterpret behaviours. A campaign that resonates in one market may fall flat in another. Human marketers bring that cultural sensitivity, shaping messages to suit different contexts.
For global brands, this balance between AI’s efficiency and human cultural insight is essential.
Marketing Strategists and Campaign Planners
AI can provide valuable insights and data, but it doesn’t understand the creative risk or brand values that go into planning a campaign. Human strategists interpret AI-driven insights to craft cohesive campaigns that go beyond audience segmentation, fostering real connections and brand affinity.
The Hybrid Model: Humans and AI in Harmony
The future of marketing will likely be a blend of AI-driven efficiency and human creativity. AI will handle data-heavy and routine tasks, giving marketing teams the time to focus on big-picture strategy and storytelling.
A hybrid model lets AI do what it does best while preserving the human touch that makes marketing truly effective.
6 Key Challenges in AI Integration for CMOs
- 1. Data Quality and Management: AI relies on accurate data, but fragmented or inconsistent data can lead to flawed insights. CMOs need solid data management practices to ensure AI has reliable information, and they need to address privacy and compliance concerns to maintain consumer trust.
- 2. Closing the Skills Gap: As AI tools become more common, CMOs face a gap in AI marketing skills within their teams. Closing this gap requires a commitment to learning and a culture that encourages experimentation with AI tools. Upskilling is crucial to make the most of AI’s capabilities.
- 3. Choosing the Right Tools: The abundance of AI tools can be overwhelming. CMOs must find the tools that align with the brand’s needs, integrate with existing systems, and enhance workflows rather than complicate them. It’s all about finding what fits.
- 4. Balancing AI Insights with Creativity: AI can suggest creative elements that perform well, but if we rely on it too much, we risk creating campaigns that all feel the same. The CMO ensures there’s a balance, using AI to guide decisions while keeping the brand’s originality intact.
- 5. Ethical AI Use: Consumers expect brands to use AI responsibly. CMOs have to establish clear ethical guidelines for AI, including regular audits to check for biases and ensure the brand remains trustworthy and fair.
- 6. Proving ROI: AI implementations aren’t cheap, so demonstrating ROI is vital. CMOs need to set measurable goals for each AI tool, ensuring that every investment in AI supports the brand’s strategic objectives.
Strategies for Effective AI Integration in Marketing
- Encouraging Experimentation: CMOs can foster a culture of experimentation, encouraging teams to try AI tools and see what works. It’s all about learning through testing and allowing room for innovation.
- Maintaining Data Integrity and Morals: Strong data practices are essential for effective AI. Regular checks for accuracy and bias, plus transparent AI use, help maintain consumer trust and brand credibility.
- Phased AI Adoption: Gradual implementation allows teams to get comfortable with AI tools without overwhelming them. Starting small and scaling up based on feedback and results ensures AI adoption is smooth and effective.
- Cross-Departmental Collaboration: Effective AI use involves teamwork across departments. Working closely with IT, legal, and data science teams ensures AI adoption aligns with compliance and tech requirements, creating a streamlined experience for everyone.
Why Humans Are Ultimately Irreplaceable in a CMO Role
- Big-Picture Thinking and Brand Leadership: A CMO’s strategic vision goes beyond data and metrics. They set the direction for the brand, ensuring all marketing aligns with the company’s goals and values. AI may help execute, but it doesn’t guide or inspire.
- Empathy and Creativity: CMOs understand what motivates consumers on a personal level. This empathy, combined with a creative touch, turns data into stories that resonate emotionally. AI can support creativity, but it can’t fully replace the empathy that brings campaigns to life.
- Adaptability and Context: Markets change fast, and a CMO’s ability to adjust campaigns to fit new cultural trends or societal changes keeps the brand relevant. AI depends on past data and often struggles to adapt to the new, something a CMO does with ease.
So What Does This All Mean… Will AI Replace the CMO Role?
Human qualities like creativity, emotional intelligence, and strategic oversight are what truly connect brands with people.
AI will continue to reshape marketing, but the role of the CMO—and their team—is more vital than ever.
The future of marketing is a collaborative one, where AI enhances human insight to create campaigns that are not only effective but meaningful.
Join the Conversation
What do you think about the future of AI in marketing? How do you see the role of CMOs evolving with advancements in AI? Share your thoughts in the comments below and subscribe for updates on AI and AGI developments here. We’d love to hear your insights!
You may also like:
- AI Content: A Ticking Time Bomb for CMOs?
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Author
-
Adrian is an AI, marketing, and technology strategist based in Asia, with over 25 years of experience in the region. Originally from the UK, he has worked with some of the world’s largest tech companies and successfully built and sold several tech businesses. Currently, Adrian leads commercial strategy and negotiations at one of ASEAN’s largest AI companies. Driven by a passion to empower startups and small businesses, he dedicates his spare time to helping them boost performance and efficiency by embracing AI tools. His expertise spans growth and strategy, sales and marketing, go-to-market strategy, AI integration, startup mentoring, and investments. View all posts
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