Navigating the AI revolution in media sales: challenges, trust and harnessing custom AI solutions
In today’s fast-paced era of resource optimization, the quick evolution of artificial intelligence (AI) is not only reshaping industries but is already making a significant impact in the media realm. Leading this transformative wave are Large Language Models (LLMs) like ChatGPT.
These new tools are already revolutionizing media sales by addressing existing resource constraints and boosting operational efficiency. These AI tools are a game-changer for sales teams, allowing them to automate a wide range of tasks, from routine administrative work to more complex data analysis.
This automation streamlines workflows and frees up valuable time for sales teams to focus on more impactful tasks.
Moreover, AI’s advanced data processing abilities enable sales teams to analyze trends and customer data more effectively, leading to more informed decision-making and targeted sales strategies. Creating personalized, relevant content has become more efficient with AI, enhancing engagement with potential clients and improving the success rates of marketing campaigns. In lead generation, AI tools are already making strides by identifying potential leads through pattern recognition and predictive analysis, further optimizing the sales process.
Looking ahead, the potential of AI in media sales is vast. It could revolutionize customer relationship management, refine predictive analytics for forecasting sales trends, and even aid in developing more nuanced sales strategies based on real-time data.
As these technologies continue to mature, they promise to open up new avenues for innovation in media sales, empowering teams to not only meet but exceed their sales goals in an increasingly digital world.
Yet, the recent turbulence at OpenAI in November, particularly the leadership changes involving Sam Altman, underscore the urgency for companies to adopt a strategic and balanced approach to AI adoption. Questions about stability and reliability are now at the forefront, necessitating a careful approach to utilizing third-party AI tools like ChatGPT. While OpenAI dealt with leadership challenges, their products went offline, shutting down numerous businesses and features across all their customers.
In what seemed like a knee-jerk reaction to the bad press, they expedited a product feature release to create a distraction. This fast pace and uncertain future surrounding LLMs makes it crucial for media companies to evaluate the long-term reliability and ethical implications of these tools.
Data Privacy and Protecting IP
Data privacy takes on heightened significance with the quick adoption of tools like ChatGPT. It’s essential to understand that any content entered into ChatGPT’s web or mobile interfaces may be leveraged to train future models, potentially contributing to its expanding knowledge base.
This underscores the adage that “if the product is free, you are the product,” drawing a parallel to how social media platforms utilize user data for various approaches to revenue generation like targeted advertising. Similarly, OpenAI uses its widely adopted solution to gather valuable data for future model training and improvements.
Consequently, companies must be vigilant in safeguarding sensitive and proprietary information. Internal data usage policies are essential safeguards against unauthorized intellectual property use, ensuring adherence to data privacy standards within the ever-evolving AI landscape.
OpenAI has recently assured its customers that inputs and outputs from their APIs will not be used for training future models. While this provides a means to utilize GPT without contributing to its training data, it requires a level of trust in OpenAI to uphold this promise. Moreover, using these API services necessitates development resources and continual maintenance, given the trajectory of these technologies.
Companies must also stay vigilant in understanding OpenAI’s frequently changing terms of service and privacy policies, which have undergone several revisions since ChatGPT’s public release nearly a year ago.
Planning for AI Hallucination
Generative AI, crucial for content creation and streamlining processes, faces the challenge of AI hallucination. This phenomenon occurs when AI generates false or misleading information, often due to limitations in its training data or interpretation of input queries. While it’s assumed that the risk of hallucinations will decrease as models improve, we are not yet at that stage.
We’re in the early phases of our journey towards Artificial General Intelligence (AGI), where such issues remain prevalent. Therefore, companies must implement robust processes for reviewing AI-generated content, focusing on identifying and correcting inaccuracies or biases. This strategy is vital for maintaining content quality and building and sustaining audience trust in an AI-centric media environment.
AI is More Than Just ChatGPT
With companies like OpenAI, Microsoft, Google, and Facebook recently taking up much of the news about this space, AI is more than just LLMs. Artificial intelligence is considered an umbrella term for many things like machine learning and more.
In response to the challenges and risks of trusting LLMs, custom AI solutions emerge as a viable alternative. Tailored to specific needs, custom AI models offer more control and align more closely with individual company goals, presenting a more secure and reliable option compared to generic third-party AI tools.
Companies can benefit from partnering with AI solution providers like ShareBuilders, who offer customized AI solutions like Precision Pending and Smart Forecasts to empower their sales teams and help save them time.
The ShareBuilder Approach to Assisting Media Companies with AI
Amidst the rapid evolution of AI, the ShareBuilders data science team offers a distinct approach to helping media companies harness AI’s potential. Its members focus on custom AI solutions like Precision Pending and Smart Forecasts, tailored to the unique needs of media sales, without needing third-party AI solutions.
These tools empower sales teams, streamline processes, and offer control and alignment with company goals not always achievable with generic third-party AI tools.
ShareBuilders prioritizes customer data safety, offering clear communication about in-house and third-party AI tools. This includes building solutions with powerful LLMs from OpenAI when necessary while providing customers the option to opt in to share their data, ensuring transparency and control.
ShareBuilders also commits to anonymizing as much data as possible when using these third-party services to help protect their customer’s privacy while still benefiting from these robust solutions.
ShareBuilders’ commitment to custom and meaningful solutions positions the company to assist media companies in navigating the AI-driven future, balancing innovation with a strategic and cautious approach.
As AI reshapes the media industry, companies like ShareBuilders play a crucial role in guiding this innovation.
To learn more about how ShareBuilders is using AI to boost the success of media sales team while protecting customers against the potential downsides of this rapidly evolving, powerful technology, please contact us here.